
R version 2.11.1 (2010-05-31)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> source("pscore_estimation_core1.R")
Loading required package: gbm
Loading required package: survival
Loading required package: splines
Loading required package: lattice
Loaded gbm 1.6-3.1 
Loading required package: survey

Attaching package: 'survey'

The following object(s) are masked from 'package:graphics':

    dotchart

Loading required package: xtable
Loading required package: MASS
Loading required package: mlbench
Loading required package: nnet
Loading required package: class

Attaching package: 'ipred'

The following object(s) are masked from 'package:survey':

    cv

randomForest 4.5-36
Type rfNews() to see new features/changes/bug fixes.
> library(Matching)
Loading required package: rgenoud
##  rgenoud (Version 5.6-7, Build Date: 2010-06-01)
##  See http://sekhon.berkeley.edu/rgenoud for additional documentation.
## 
##  Matching (Version 4.7-10, Build Date: 2010/08/13)
##  See http://sekhon.berkeley.edu/matching for additional documentation.
##  Please cite software as:
##   Jasjeet S. Sekhon. Forthcoming. ``Multivariate and Propensity Score Matching
##   Software with Automated Balance Optimization: The Matching package for R.''
##   Journal of Statistical Software. 
##
> 
> load(file="RData.simdata.F.obs1000.reps1000")
> dta <- simdata.F.obs1000.reps1000
> rm(simdata.F.obs1000.reps1000)
> gc()
           used (Mb) gc trigger  (Mb) max used (Mb)
Ncells   200675 10.8     407500  21.8   350000 18.7
Vcells 12195008 93.1   13300721 101.5 12195672 93.1
> 
> #true estimate
> g1 <- -0.4
> 
> sims <- dim(dta)[2]
> nobs <- length(dta[1,2]$w1)
> 
> true.est <- matrix(0, nrow=sims, ncol=1)
> 
> logit.pscore <- list()
> logit.est <- matrix(0, nrow=sims, ncol=1)
> logit.nSE <- matrix(0, nrow=sims, ncol=1)
> logit.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> boosting.pscore <- list()
> boosting.desc <- list()
> boosting.est <- matrix(0, nrow=sims, ncol=1)
> boosting.nSE <- matrix(0, nrow=sims, ncol=1)
> boosting.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> forest.pscore <- list()
> forest.est <- matrix(0, nrow=sims, ncol=1)
> forest.nSE <- matrix(0, nrow=sims, ncol=1)
> forest.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> nnet.pscore <- list()
> nnet.est <- matrix(0, nrow=sims, ncol=1)
> nnet.nSE <- matrix(0, nrow=sims, ncol=1)
> nnet.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> count <- 0
> for (s in 1:sims)
+   {
+     cat("\n\ns:",s,"\n")
+     count <- count+1
+ 
+     sdta <- as.data.frame(dta[,s])
+ 
+     #true model
+ #    lm1 <- lm(y.a~ z.a+ w1 + w2 + w3 + w4 + w8 + w9 + w10, data=sdta)
+ #    true.est[s] <- lm1$coef[2]
+ #    cat("truth:",mean(true.est[1:s]),"\n")
+ 
+     #logit
+     logit.ps <- glm(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, data=sdta, family=binomial(link="logit"))$fitted
+     logit.pscore[[s]] <- logit.ps
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=logit.ps, estimand="ATT", M=1)
+     logit.est[s] <-  m1$est
+     logit.nSE[s] <- m1$se.standard
+     logit.aiSE[s] <- m1$se
+ 
+     cat("logit",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("logit mean",s,":",mean(logit.est[1:s]),"\n")
+         rmse <- sqrt(mean((logit.est[1:s]-g1)^2))
+         cat("logit RMSE",s,":",rmse,"\n")
+       }
+ 
+     #boosting!
+     ps.model <- ps(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10,
+                    data=sdta, title="none", stop.method=stop.methods["ks.stat.mean"],
+                    plots="none", pdf.plots=F, n.trees=20000, interaction.depth=4,
+                    shrinkage=0.0005, verbose=FALSE)
+ 
+     boosting.pscore[[s]] <- ps.model$ps
+     boosting.desc[[s]] <- ps.model$desc
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=ps.model$ps, estimand="ATT", M=1)
+     boosting.est[s] <-  m1$est
+     boosting.nSE[s] <- m1$se.standard
+     boosting.aiSE[s] <- m1$se
+ 
+     cat("\nboosting",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("boosting mean",s,":",mean(boosting.est[1:s]),"\n")
+         rmse <- sqrt(mean((boosting.est[1:s]-g1)^2))
+         cat("boosting RMSE",s,":",rmse,"\n")
+       }    
+ 
+ 
+     #Random Forest
+     ps1 <- 1
+     while (max(ps1)> .999) {
+ #      gc(verbose=TRUE)
+       fps.model <- randomForest(as.factor(z.a) ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, data=sdta)
+       ps1 <- fps.model$votes[, 2]
+     }
+     
+     forest.pscore[[s]] <- ps1
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=ps1, estimand="ATT", M=1)
+     forest.est[s] <-  m1$est
+     forest.nSE[s] <- m1$se.standard
+     forest.aiSE[s] <- m1$se
+ 
+     cat("\nforest",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("forest mean",s,":",mean(forest.est[1:s]),"\n")
+         rmse <- sqrt(mean((forest.est[1:s]-g1)^2))
+         cat("forest RMSE",s,":",rmse,"\n")
+       }
+ 
+     n1 <- nnet(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, size=40, data=sdta, trace=FALSE)
+     nnet.pscore[[s]] <- n1$fitted.values
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=n1$fitted.values, estimand="ATT", M=1)
+     nnet.est[s] <-  m1$est
+     nnet.nSE[s] <- m1$se.standard
+     nnet.aiSE[s] <- m1$se
+ 
+     cat("\nnnet",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("nnet mean",s,":",mean(nnet.est[1:s]),"\n")
+         rmse <- sqrt(mean((nnet.est[1:s]-g1)^2))
+         cat("nnet RMSE",s,":",rmse,"\n")
+       }    
+ 
+     if (count>50)
+       {
+         save.image("RData.sims.F.nobs1000")
+         count <- 0
+       }
+   }#end of sims loop


s: 1 
logit 1 : -0.4099060 

boosting 1 : -0.641666 

forest 1 : -0.4782524 

nnet 1 : -0.4656329 


s: 2 
logit 2 : -0.424293 
logit mean 2 : -0.4170995 
logit RMSE 2 : 0.01855098 

boosting 2 : -0.5316037 
boosting mean 2 : -0.5866348 
boosting RMSE 2 : 0.1945790 

forest 2 : -0.3814719 
forest mean 2 : -0.4298622 
forest RMSE 2 : 0.05686267 

nnet 2 : -0.4795113 
nnet mean 2 : -0.4725721 
nnet RMSE 2 : 0.07290311 


s: 3 
logit 3 : -0.4596517 
logit mean 3 : -0.4312835 
logit RMSE 3 : 0.03762358 

boosting 3 : -0.4115433 
boosting mean 3 : -0.528271 
boosting RMSE 3 : 0.1590128 

forest 3 : -0.3958386 
forest mean 3 : -0.418521 
forest RMSE 3 : 0.04649029 

nnet 3 : -0.4953655 
nnet mean 3 : -0.4801699 
nnet RMSE 3 : 0.08108496 


s: 4 
logit 4 : -0.3386335 
logit mean 4 : -0.408121 
logit RMSE 4 : 0.04475614 

boosting 4 : -0.3858886 
boosting mean 4 : -0.4926754 
boosting RMSE 4 : 0.1378898 

forest 4 : -0.3738605 
forest mean 4 : -0.4073559 
forest RMSE 4 : 0.04233001 

nnet 4 : -0.4742276 
nnet mean 4 : -0.4786843 
nnet RMSE 4 : 0.07942615 


s: 5 
logit 5 : -0.4589056 
logit mean 5 : -0.4182779 
logit RMSE 5 : 0.04792142 

boosting 5 : -0.4669023 
boosting mean 5 : -0.4875208 
boosting RMSE 5 : 0.1269096 

forest 5 : -0.3783536 
forest mean 5 : -0.4015554 
forest RMSE 5 : 0.03907911 

nnet 5 : -0.3067318 
nnet mean 5 : -0.4442938 
nnet RMSE 5 : 0.08238085 


s: 6 
logit 6 : -0.4377328 
logit mean 6 : -0.4215204 
logit RMSE 6 : 0.04637902 

boosting 6 : -0.3725085 
boosting mean 6 : -0.4683521 
boosting RMSE 6 : 0.1163945 

forest 6 : -0.3670651 
forest mean 6 : -0.395807 
forest RMSE 6 : 0.03812391 

nnet 6 : -0.5703776 
nnet mean 6 : -0.4653078 
nnet RMSE 6 : 0.1024382 


s: 7 
logit 7 : -0.4340394 
logit mean 7 : -0.4233088 
logit RMSE 7 : 0.04482468 

boosting 7 : -0.4250938 
boosting mean 7 : -0.4621723 
boosting RMSE 7 : 0.1081769 

forest 7 : -0.5015345 
forest mean 7 : -0.4109109 
forest RMSE 7 : 0.05213972 

nnet 7 : -0.3945103 
nnet mean 7 : -0.4551939 
nnet RMSE 7 : 0.09486206 


s: 8 
logit 8 : -0.5318667 
logit mean 8 : -0.4368786 
logit RMSE 8 : 0.06270326 

boosting 8 : -0.4327097 
boosting mean 8 : -0.4584895 
boosting RMSE 8 : 0.1018489 

forest 8 : -0.3198837 
forest mean 8 : -0.3995325 
forest RMSE 8 : 0.05640089 

nnet 8 : -0.5796842 
nnet mean 8 : -0.4707552 
nnet RMSE 8 : 0.1091319 


s: 9 
logit 9 : -0.4006504 
logit mean 9 : -0.4328532 
logit RMSE 9 : 0.0591176 

boosting 9 : -0.5285409 
boosting mean 9 : -0.466273 
boosting RMSE 9 : 0.1051499 

forest 9 : -0.3779422 
forest mean 9 : -0.3971336 
forest RMSE 9 : 0.05368119 

nnet 9 : -0.2318487 
nnet mean 9 : -0.44421 
nnet RMSE 9 : 0.117167 


s: 10 
logit 10 : -0.3282198 
logit mean 10 : -0.4223899 
logit RMSE 10 : 0.06050323 

boosting 10 : -0.4941619 
boosting mean 10 : -0.4690619 
boosting RMSE 10 : 0.1041033 

forest 10 : -0.4471095 
forest mean 10 : -0.4021312 
forest RMSE 10 : 0.05306066 

nnet 10 : -0.5378899 
nnet mean 10 : -0.453578 
nnet RMSE 10 : 0.1194012 


s: 11 
logit 11 : -0.4133655 
logit mean 11 : -0.4215695 
logit RMSE 11 : 0.05782815 

boosting 11 : -0.5451125 
boosting mean 11 : -0.4759756 
boosting RMSE 11 : 0.1084739 

forest 11 : -0.3317565 
forest mean 11 : -0.3957335 
forest RMSE 11 : 0.05461561 

nnet 11 : -0.4487714 
nnet mean 11 : -0.453141 
nnet RMSE 11 : 0.1147904 


s: 12 
logit 12 : -0.4785984 
logit mean 12 : -0.4263219 
logit RMSE 12 : 0.05983501 

boosting 12 : -0.3999686 
boosting mean 12 : -0.4696416 
boosting RMSE 12 : 0.1038559 

forest 12 : -0.2688823 
forest mean 12 : -0.3851626 
forest RMSE 12 : 0.0645519 

nnet 12 : -0.5039008 
nnet mean 12 : -0.457371 
nnet RMSE 12 : 0.1139227 


s: 13 
logit 13 : -0.4782309 
logit mean 13 : -0.4303149 
logit RMSE 13 : 0.06144592 

boosting 13 : -0.4528125 
boosting mean 13 : -0.4683471 
boosting RMSE 13 : 0.1008509 

forest 13 : -0.3603361 
forest mean 13 : -0.3832528 
forest RMSE 13 : 0.06298754 

nnet 13 : -0.4565311 
nnet mean 13 : -0.4573064 
nnet RMSE 13 : 0.1105707 


s: 14 
logit 14 : -0.5093738 
logit mean 14 : -0.4359620 
logit RMSE 14 : 0.06603324 

boosting 14 : -0.7164598 
boosting mean 14 : -0.4860694 
boosting RMSE 14 : 0.1288322 

forest 14 : -0.4270784 
forest mean 14 : -0.3863832 
forest RMSE 14 : 0.06112624 

nnet 14 : -0.5568635 
nnet mean 14 : -0.4644176 
nnet RMSE 14 : 0.1144997 


s: 15 
logit 15 : -0.4296938 
logit mean 15 : -0.4355441 
logit RMSE 15 : 0.06425323 

boosting 15 : -0.5720265 
boosting mean 15 : -0.4917999 
boosting RMSE 15 : 0.1321518 

forest 15 : -0.3641783 
forest mean 15 : -0.3849029 
forest RMSE 15 : 0.05977348 

nnet 15 : -0.4457834 
nnet mean 15 : -0.4631753 
nnet RMSE 15 : 0.1112471 


s: 16 
logit 16 : -0.5194682 
logit mean 16 : -0.4407893 
logit RMSE 16 : 0.06901078 

boosting 16 : -0.6186755 
boosting mean 16 : -0.4997296 
boosting RMSE 16 : 0.1391448 

forest 16 : -0.3784020 
forest mean 16 : -0.3844966 
forest RMSE 16 : 0.05812675 

nnet 16 : -0.6271823 
nnet mean 16 : -0.4734258 
nnet RMSE 16 : 0.1217709 


s: 17 
logit 17 : -0.4087817 
logit mean 17 : -0.4389065 
logit RMSE 17 : 0.06698416 

boosting 17 : -0.4051236 
boosting mean 17 : -0.4941646 
boosting RMSE 17 : 0.1349960 

forest 17 : -0.4096907 
forest mean 17 : -0.3859786 
forest RMSE 17 : 0.05644019 

nnet 17 : -0.3810263 
nnet mean 17 : -0.4679905 
nnet RMSE 17 : 0.1182247 


s: 18 
logit 18 : -0.4377943 
logit mean 18 : -0.4388447 
logit RMSE 18 : 0.0657036 

boosting 18 : -0.6366007 
boosting mean 18 : -0.5020777 
boosting RMSE 18 : 0.1425534 

forest 18 : -0.4602888 
forest mean 18 : -0.3901069 
forest RMSE 18 : 0.05666086 

nnet 18 : -0.4575379 
nnet mean 18 : -0.4674098 
nnet RMSE 18 : 0.1156914 


s: 19 
logit 19 : -0.3806491 
logit mean 19 : -0.4357818 
logit RMSE 19 : 0.06410509 

boosting 19 : -0.6174974 
boosting mean 19 : -0.5081524 
boosting RMSE 19 : 0.1474506 

forest 19 : -0.3163503 
forest mean 19 : -0.386225 
forest RMSE 19 : 0.05839314 

nnet 19 : -0.2752419 
nnet mean 19 : -0.4572957 
nnet RMSE 19 : 0.1161862 


s: 20 
logit 20 : -0.3333199 
logit mean 20 : -0.4306587 
logit RMSE 20 : 0.0642363 

boosting 20 : -0.509811 
boosting mean 20 : -0.5082353 
boosting RMSE 20 : 0.1457996 

forest 20 : -0.4270932 
forest mean 20 : -0.3882684 
forest RMSE 20 : 0.05723612 

nnet 20 : -0.3018822 
nnet mean 20 : -0.449525 
nnet RMSE 20 : 0.1153501 


s: 21 
logit 21 : -0.4017525 
logit mean 21 : -0.4292822 
logit RMSE 21 : 0.06268937 

boosting 21 : -0.4912593 
boosting mean 21 : -0.5074269 
boosting RMSE 21 : 0.1436727 

forest 21 : -0.3938612 
forest mean 21 : -0.3885348 
forest RMSE 21 : 0.05587279 

nnet 21 : -0.3572109 
nnet mean 21 : -0.4451291 
nnet RMSE 21 : 0.1129567 


s: 22 
logit 22 : -0.4676956 
logit mean 22 : -0.4310283 
logit RMSE 22 : 0.06292557 

boosting 22 : -0.5433964 
boosting mean 22 : -0.5090619 
boosting RMSE 22 : 0.1436601 

forest 22 : -0.5136227 
forest mean 22 : -0.3942206 
forest RMSE 22 : 0.05972181 

nnet 22 : -0.6729227 
nnet mean 22 : -0.4554834 
nnet RMSE 22 : 0.1247599 


s: 23 
logit 23 : -0.3989385 
logit mean 23 : -0.4296331 
logit RMSE 23 : 0.06154282 

boosting 23 : -0.4932687 
boosting mean 23 : -0.5083753 
boosting RMSE 23 : 0.1418419 

forest 23 : -0.4127031 
forest mean 23 : -0.3950242 
forest RMSE 23 : 0.05846911 

nnet 23 : -0.1862859 
nnet mean 23 : -0.4437791 
nnet RMSE 23 : 0.1299003 


s: 24 
logit 24 : -0.5119652 
logit mean 24 : -0.4330636 
logit RMSE 24 : 0.06443638 

boosting 24 : -0.6993132 
boosting mean 24 : -0.516331 
boosting RMSE 24 : 0.1517026 

forest 24 : -0.4254047 
forest mean 24 : -0.39629 
forest RMSE 24 : 0.05747247 

nnet 24 : -0.630796 
nnet mean 24 : -0.4515715 
nnet RMSE 24 : 0.1356114 


s: 25 
logit 25 : -0.4788184 
logit mean 25 : -0.4348938 
logit RMSE 25 : 0.06507272 

boosting 25 : -0.5767895 
boosting mean 25 : -0.5187493 
boosting RMSE 25 : 0.1527852 

forest 25 : -0.4724824 
forest mean 25 : -0.3993377 
forest RMSE 25 : 0.05814731 

nnet 25 : -0.354853 
nnet mean 25 : -0.4477028 
nnet RMSE 25 : 0.1331780 


s: 26 
logit 26 : -0.4428925 
logit mean 26 : -0.4352014 
logit RMSE 26 : 0.06436113 

boosting 26 : -0.4263485 
boosting mean 26 : -0.5151955 
boosting RMSE 26 : 0.1499073 

forest 26 : -0.4460301 
forest mean 26 : -0.4011336 
forest RMSE 26 : 0.05772831 

nnet 26 : -0.3952379 
nnet mean 26 : -0.4456849 
nnet RMSE 26 : 0.1305951 


s: 27 
logit 27 : -0.4577696 
logit mean 27 : -0.4360373 
logit RMSE 27 : 0.06412908 

boosting 27 : -0.5714324 
boosting mean 27 : -0.5172783 
boosting RMSE 27 : 0.1507594 

forest 27 : -0.3750633 
forest mean 27 : -0.400168 
forest RMSE 27 : 0.0568521 

nnet 27 : -0.5354152 
nnet mean 27 : -0.4490082 
nnet RMSE 27 : 0.1307768 


s: 28 
logit 28 : -0.4324902 
logit mean 28 : -0.4359106 
logit RMSE 28 : 0.06327214 

boosting 28 : -0.6583474 
boosting mean 28 : -0.5223165 
boosting RMSE 28 : 0.1558857 

forest 28 : -0.2188559 
forest mean 28 : -0.3936926 
forest RMSE 28 : 0.0654876 

nnet 28 : -0.3333261 
nnet mean 28 : -0.4448767 
nnet RMSE 28 : 0.1290369 


s: 29 
logit 29 : -0.4663146 
logit mean 29 : -0.436959 
logit RMSE 29 : 0.06337948 

boosting 29 : -0.5908263 
boosting mean 29 : -0.5246789 
boosting RMSE 29 : 0.1572199 

forest 29 : -0.3840909 
forest mean 29 : -0.3933615 
forest RMSE 29 : 0.06441638 

nnet 29 : -0.37596 
nnet mean 29 : -0.4425003 
nnet RMSE 29 : 0.1268712 


s: 30 
logit 30 : -0.3891709 
logit mean 30 : -0.4353661 
logit RMSE 30 : 0.06234556 

boosting 30 : -0.484093 
boosting mean 30 : -0.523326 
boosting RMSE 30 : 0.1553379 

forest 30 : -0.4302498 
forest mean 30 : -0.3945911 
forest RMSE 30 : 0.06357402 

nnet 30 : -0.4489307 
nnet mean 30 : -0.4427146 
nnet RMSE 30 : 0.1250582 


s: 31 
logit 31 : -0.4568425 
logit mean 31 : -0.4360589 
logit RMSE 31 : 0.06217565 

boosting 31 : -0.5729503 
boosting mean 31 : -0.5249268 
boosting RMSE 31 : 0.1559371 

forest 31 : -0.3128514 
forest mean 31 : -0.3919543 
forest RMSE 31 : 0.06446919 

nnet 31 : -0.5970602 
nnet mean 31 : -0.4476935 
nnet RMSE 31 : 0.1280145 


s: 32 
logit 32 : -0.4618977 
logit mean 32 : -0.4368663 
logit RMSE 32 : 0.06216698 

boosting 32 : -0.4662011 
boosting mean 32 : -0.5230916 
boosting RMSE 32 : 0.1539268 

forest 32 : -0.4253269 
forest mean 32 : -0.3929972 
forest RMSE 32 : 0.06361162 

nnet 32 : -0.3149841 
nnet mean 32 : -0.4435464 
nnet RMSE 32 : 0.1268916 


s: 33 
logit 33 : -0.4151756 
logit mean 33 : -0.436209 
logit RMSE 33 : 0.06127478 

boosting 33 : -0.4156996 
boosting mean 33 : -0.5198373 
boosting RMSE 33 : 0.1516012 

forest 33 : -0.3334213 
forest mean 33 : -0.3911919 
forest RMSE 33 : 0.06370356 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 33 : -0.1986233 
nnet mean 33 : -0.4361244 
nnet RMSE 33 : 0.1297783 


s: 34 
logit 34 : -0.3828965 
logit mean 34 : -0.434641 
logit RMSE 34 : 0.06043818 

boosting 34 : -0.4134396 
boosting mean 34 : -0.516708 
boosting RMSE 34 : 0.1493730 

forest 34 : -0.3759117 
forest mean 34 : -0.3907425 
forest RMSE 34 : 0.06289557 

nnet 34 : -0.4583304 
nnet mean 34 : -0.4367776 
nnet RMSE 34 : 0.1282463 


s: 35 
logit 35 : -0.4791292 
logit mean 35 : -0.4359121 
logit RMSE 35 : 0.06105167 

boosting 35 : -0.5196113 
boosting mean 35 : -0.5167909 
boosting RMSE 35 : 0.1486054 

forest 35 : -0.4384177 
forest mean 35 : -0.3921046 
forest RMSE 35 : 0.06232974 

nnet 35 : -0.4342961 
nnet mean 35 : -0.4367067 
nnet RMSE 35 : 0.1265338 


s: 36 
logit 36 : -0.3491282 
logit mean 36 : -0.4335014 
logit RMSE 36 : 0.06079192 

boosting 36 : -0.4556992 
boosting mean 36 : -0.515094 
boosting RMSE 36 : 0.1468206 

forest 36 : -0.334454 
forest mean 36 : -0.3905032 
forest RMSE 36 : 0.06242132 

nnet 36 : -0.3641501 
nnet mean 36 : -0.4346912 
nnet RMSE 36 : 0.1249070 


s: 37 
logit 37 : -0.3433103 
logit mean 37 : -0.4310638 
logit RMSE 37 : 0.06068469 

boosting 37 : -0.2119958 
boosting mean 37 : -0.5069021 
boosting RMSE 37 : 0.1480844 

forest 37 : -0.4276007 
forest mean 37 : -0.3915059 
forest RMSE 37 : 0.06173898 

nnet 37 : -0.4121953 
nnet mean 37 : -0.4340832 
nnet RMSE 37 : 0.1232238 


s: 38 
logit 38 : -0.3581806 
logit mean 38 : -0.4291459 
logit RMSE 38 : 0.06026395 

boosting 38 : -0.4074522 
boosting mean 38 : -0.504285 
boosting RMSE 38 : 0.1461279 

forest 38 : -0.5165071 
forest mean 38 : -0.3947954 
forest RMSE 38 : 0.0637856 

nnet 38 : -0.477792 
nnet mean 38 : -0.4352334 
nnet RMSE 38 : 0.1222448 


s: 39 
logit 39 : -0.3567384 
logit mean 39 : -0.4272893 
logit RMSE 39 : 0.05988832 

boosting 39 : -0.3881721 
boosting mean 39 : -0.5013078 
boosting RMSE 39 : 0.1442547 

forest 39 : -0.3412630 
forest mean 39 : -0.3934227 
forest RMSE 39 : 0.06366114 

nnet 39 : -0.2099120 
nnet mean 39 : -0.429456 
nnet RMSE 39 : 0.1244472 


s: 40 
logit 40 : -0.3380937 
logit mean 40 : -0.4250594 
logit RMSE 40 : 0.0599396 

boosting 40 : -0.2843762 
boosting mean 40 : -0.4958845 
boosting RMSE 40 : 0.1436086 

forest 40 : -0.359894 
forest mean 40 : -0.3925845 
forest RMSE 40 : 0.06317939 

nnet 40 : -0.2745016 
nnet mean 40 : -0.4255821 
nnet RMSE 40 : 0.1244736 


s: 41 
logit 41 : -0.4147252 
logit mean 41 : -0.4248073 
logit RMSE 41 : 0.05924876 

boosting 41 : -0.2743035 
boosting mean 41 : -0.4904801 
boosting RMSE 41 : 0.1431983 

forest 41 : -0.3259757 
forest mean 41 : -0.3909599 
forest RMSE 41 : 0.06346595 

nnet 41 : -0.5995098 
nnet mean 41 : -0.4298242 
nnet RMSE 41 : 0.1268330 


s: 42 
logit 42 : -0.5012057 
logit mean 42 : -0.4266263 
logit RMSE 42 : 0.06058635 

boosting 42 : -0.4310351 
boosting mean 42 : -0.4890647 
boosting RMSE 42 : 0.1415643 

forest 42 : -0.4103489 
forest mean 42 : -0.3914216 
forest RMSE 42 : 0.06272618 

nnet 42 : -0.5268457 
nnet mean 42 : -0.4321343 
nnet RMSE 42 : 0.1268333 


s: 43 
logit 43 : -0.3379497 
logit mean 43 : -0.4245641 
logit RMSE 43 : 0.0606208 

boosting 43 : -0.4526693 
boosting mean 43 : -0.4882183 
boosting RMSE 43 : 0.1401389 

forest 43 : -0.2941169 
forest mean 43 : -0.3891587 
forest RMSE 43 : 0.06406089 

nnet 43 : -0.4043020 
nnet mean 43 : -0.431487 
nnet RMSE 43 : 0.1253516 


s: 44 
logit 44 : -0.3980172 
logit mean 44 : -0.4239607 
logit RMSE 44 : 0.05992871 

boosting 44 : -0.3539895 
boosting mean 44 : -0.4851676 
boosting RMSE 44 : 0.1387108 

forest 44 : -0.3609225 
forest mean 44 : -0.3885169 
forest RMSE 44 : 0.06360217 

nnet 44 : -0.3316798 
nnet mean 44 : -0.4292187 
nnet RMSE 44 : 0.1243462 


s: 45 
logit 45 : -0.4526774 
logit mean 45 : -0.4245989 
logit RMSE 45 : 0.05977713 

boosting 45 : -0.3015279 
boosting mean 45 : -0.4810868 
boosting RMSE 45 : 0.1379442 

forest 45 : -0.3946516 
forest mean 45 : -0.3886533 
forest RMSE 45 : 0.06289656 

nnet 45 : -0.5401576 
nnet mean 45 : -0.431684 
nnet RMSE 45 : 0.1247194 


s: 46 
logit 46 : -0.598468 
logit mean 46 : -0.4283787 
logit RMSE 46 : 0.06596908 

boosting 46 : -0.6573378 
boosting mean 46 : -0.4849183 
boosting RMSE 46 : 0.1416141 

forest 46 : -0.3789015 
forest mean 46 : -0.3884413 
forest RMSE 46 : 0.06228687 

nnet 46 : -0.678684 
nnet mean 46 : -0.4370535 
nnet RMSE 46 : 0.1300198 


s: 47 
logit 47 : -0.3474028 
logit mean 47 : -0.4266558 
logit RMSE 47 : 0.0657129 

boosting 47 : -0.4603508 
boosting mean 47 : -0.4843956 
boosting RMSE 47 : 0.1403758 

forest 47 : -0.3710113 
forest mean 47 : -0.3880704 
forest RMSE 47 : 0.06176559 

nnet 47 : -0.5394503 
nnet mean 47 : -0.4392322 
nnet RMSE 47 : 0.1302275 


s: 48 
logit 48 : -0.5102905 
logit mean 48 : -0.4283982 
logit RMSE 48 : 0.06694506 

boosting 48 : -0.4874498 
boosting mean 48 : -0.4844592 
boosting RMSE 48 : 0.1394782 

forest 48 : -0.4450312 
forest mean 48 : -0.3892571 
forest RMSE 48 : 0.06146345 

nnet 48 : -0.5610809 
nnet mean 48 : -0.4417707 
nnet RMSE 48 : 0.1309445 


s: 49 
logit 49 : -0.4419516 
logit mean 49 : -0.4286748 
logit RMSE 49 : 0.06652891 

boosting 49 : -0.572832 
boosting mean 49 : -0.4862627 
boosting RMSE 49 : 0.1402382 

forest 49 : -0.4149311 
forest mean 49 : -0.3897811 
forest RMSE 49 : 0.06087042 

nnet 49 : -0.3106910 
nnet mean 49 : -0.4390956 
nnet RMSE 49 : 0.1302279 


s: 50 
logit 50 : -0.5109933 
logit mean 50 : -0.4303211 
logit RMSE 50 : 0.06770498 

boosting 50 : -0.4160489 
boosting mean 50 : -0.4848585 
boosting RMSE 50 : 0.1388473 

forest 50 : -0.3826755 
forest mean 50 : -0.3896389 
forest RMSE 50 : 0.06030843 

nnet 50 : -0.3914771 
nnet mean 50 : -0.4381432 
nnet RMSE 50 : 0.1289247 


s: 51 
logit 51 : -0.4405488 
logit mean 51 : -0.4305217 
logit RMSE 51 : 0.06727794 

boosting 51 : -0.557763 
boosting mean 51 : -0.486288 
boosting RMSE 51 : 0.1392429 

forest 51 : -0.3285776 
forest mean 51 : -0.3884417 
forest RMSE 51 : 0.06054596 

nnet 51 : -0.5774172 
nnet mean 51 : -0.4408741 
nnet RMSE 51 : 0.1300494 


s: 52 
logit 52 : -0.3879863 
logit mean 52 : -0.4297037 
logit RMSE 52 : 0.06664872 

boosting 52 : -0.480051 
boosting mean 52 : -0.486168 
boosting RMSE 52 : 0.1383436 

forest 52 : -0.389468 
forest mean 52 : -0.3884614 
forest RMSE 52 : 0.05997875 

nnet 52 : -0.6150507 
nnet mean 52 : -0.4442237 
nnet RMSE 52 : 0.1322005 


s: 53 
logit 53 : -0.464882 
logit mean 53 : -0.4303674 
logit RMSE 53 : 0.06661582 

boosting 53 : -0.5107061 
boosting mean 53 : -0.486631 
boosting RMSE 53 : 0.1378734 

forest 53 : -0.3792233 
forest mean 53 : -0.3882871 
forest RMSE 53 : 0.05947873 

nnet 53 : -0.2017595 
nnet mean 53 : -0.4396489 
nnet RMSE 53 : 0.1337487 


s: 54 
logit 54 : -0.5328135 
logit mean 54 : -0.4322646 
logit RMSE 54 : 0.0684262 

boosting 54 : -0.2680301 
boosting mean 54 : -0.4825828 
boosting RMSE 54 : 0.1377664 

forest 54 : -0.3019245 
forest mean 54 : -0.3866878 
forest RMSE 54 : 0.06041797 

nnet 54 : -0.5264443 
nnet mean 54 : -0.4412562 
nnet RMSE 54 : 0.1336170 


s: 55 
logit 55 : -0.4307679 
logit mean 55 : -0.4322374 
logit RMSE 55 : 0.0679281 

boosting 55 : -0.3167134 
boosting mean 55 : -0.479567 
boosting RMSE 55 : 0.1369694 

forest 55 : -0.3007510 
forest mean 55 : -0.3851253 
forest RMSE 55 : 0.06134378 

nnet 55 : -0.2993403 
nnet mean 55 : -0.4386759 
nnet RMSE 55 : 0.1330907 


s: 56 
logit 56 : -0.4339512 
logit mean 56 : -0.432268 
logit RMSE 56 : 0.06747158 

boosting 56 : -0.739388 
boosting mean 56 : -0.4842067 
boosting RMSE 56 : 0.1431170 

forest 56 : -0.2444696 
forest mean 56 : -0.3826136 
forest RMSE 56 : 0.06424812 

nnet 56 : -0.2670516 
nnet mean 56 : -0.4356112 
nnet RMSE 56 : 0.1330881 


s: 57 
logit 57 : -0.445512 
logit mean 57 : -0.4325003 
logit RMSE 57 : 0.06714824 

boosting 57 : -0.3551887 
boosting mean 57 : -0.4819432 
boosting RMSE 57 : 0.1419801 

forest 57 : -0.4030235 
forest mean 57 : -0.3829717 
forest RMSE 57 : 0.0636833 

nnet 57 : -0.3259634 
nnet mean 57 : -0.4336875 
nnet RMSE 57 : 0.1322795 


s: 58 
logit 58 : -0.4500249 
logit mean 58 : -0.4328025 
logit RMSE 58 : 0.06689016 

boosting 58 : -0.516669 
boosting mean 58 : -0.4825419 
boosting RMSE 58 : 0.1415821 

forest 58 : -0.4016703 
forest mean 58 : -0.3832941 
forest RMSE 58 : 0.0631323 

nnet 58 : -0.5986463 
nnet mean 58 : -0.4365316 
nnet RMSE 58 : 0.1337032 


s: 59 
logit 59 : -0.3436269 
logit mean 59 : -0.431291 
logit RMSE 59 : 0.06672571 

boosting 59 : -0.5087094 
boosting mean 59 : -0.4829855 
boosting RMSE 59 : 0.1410887 

forest 59 : -0.4192803 
forest mean 59 : -0.383904 
forest RMSE 59 : 0.0626453 

nnet 59 : -0.3331964 
nnet mean 59 : -0.4347802 
nnet RMSE 59 : 0.1328502 


s: 60 
logit 60 : -0.4006038 
logit mean 60 : -0.4307796 
logit RMSE 60 : 0.06616737 

boosting 60 : -0.5061124 
boosting mean 60 : -0.4833709 
boosting RMSE 60 : 0.1405771 

forest 60 : -0.3709249 
forest mean 60 : -0.3836877 
forest RMSE 60 : 0.06223436 

nnet 60 : -0.3572625 
nnet mean 60 : -0.4334882 
nnet RMSE 60 : 0.1318540 


s: 61 
logit 61 : -0.5161908 
logit mean 61 : -0.4321797 
logit RMSE 61 : 0.06728793 

boosting 61 : -0.4398366 
boosting mean 61 : -0.4826572 
boosting RMSE 61 : 0.1395133 

forest 61 : -0.3162320 
forest mean 61 : -0.3825818 
forest RMSE 61 : 0.06264708 

nnet 61 : -0.4048312 
nnet mean 61 : -0.4330185 
nnet RMSE 61 : 0.1307702 


s: 62 
logit 62 : -0.3999795 
logit mean 62 : -0.4316604 
logit RMSE 62 : 0.06674308 

boosting 62 : -0.4953512 
boosting mean 62 : -0.482862 
boosting RMSE 62 : 0.1389125 

forest 62 : -0.2495412 
forest mean 62 : -0.380436 
forest RMSE 62 : 0.0650114 

nnet 62 : -0.5027504 
nnet mean 62 : -0.4341432 
nnet RMSE 62 : 0.1303661 


s: 63 
logit 63 : -0.4133665 
logit mean 63 : -0.43137 
logit RMSE 63 : 0.06623266 

boosting 63 : -0.5283279 
boosting mean 63 : -0.4835836 
boosting RMSE 63 : 0.1387508 

forest 63 : -0.3958471 
forest mean 63 : -0.3806806 
forest RMSE 63 : 0.0644955 

nnet 63 : -0.3891865 
nnet mean 63 : -0.4334296 
nnet RMSE 63 : 0.1293344 


s: 64 
logit 64 : -0.3806434 
logit mean 64 : -0.4305774 
logit RMSE 64 : 0.06575771 

boosting 64 : -0.4482242 
boosting mean 64 : -0.4830312 
boosting RMSE 64 : 0.1377945 

forest 64 : -0.4471829 
forest mean 64 : -0.3817197 
forest RMSE 64 : 0.06426087 

nnet 64 : -0.2893009 
nnet mean 64 : -0.4311776 
nnet RMSE 64 : 0.1290640 


s: 65 
logit 65 : -0.5048021 
logit mean 65 : -0.4317193 
logit RMSE 65 : 0.06653217 

boosting 65 : -0.5316621 
boosting mean 65 : -0.4837793 
boosting RMSE 65 : 0.1377022 

forest 65 : -0.3499513 
forest mean 65 : -0.381231 
forest RMSE 65 : 0.0640661 

nnet 65 : -0.5755293 
nnet mean 65 : -0.4333983 
nnet RMSE 65 : 0.1299048 


s: 66 
logit 66 : -0.4480686 
logit mean 66 : -0.431967 
logit RMSE 66 : 0.0662908 

boosting 66 : -0.6221006 
boosting mean 66 : -0.4858751 
boosting RMSE 66 : 0.1393628 

forest 66 : -0.4142483 
forest mean 66 : -0.3817313 
forest RMSE 66 : 0.06360309 

nnet 66 : -0.5195755 
nnet mean 66 : -0.4347041 
nnet RMSE 66 : 0.1297544 


s: 67 
logit 67 : -0.4753128 
logit mean 67 : -0.432614 
logit RMSE 67 : 0.06643446 

boosting 67 : -0.4702019 
boosting mean 67 : -0.4856412 
boosting RMSE 67 : 0.1385845 

forest 67 : -0.3614501 
forest mean 67 : -0.3814286 
forest RMSE 67 : 0.06330209 

nnet 67 : -0.2225464 
nnet mean 67 : -0.4315375 
nnet RMSE 67 : 0.1305945 


s: 68 
logit 68 : -0.5132124 
logit mean 68 : -0.4337993 
logit RMSE 68 : 0.06735814 

boosting 68 : -0.6248861 
boosting mean 68 : -0.4876889 
boosting RMSE 68 : 0.1402390 

forest 68 : -0.3298225 
forest mean 68 : -0.3806696 
forest RMSE 68 : 0.0634086 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 68 : -0.1406587 
nnet mean 68 : -0.4272599 
nnet RMSE 68 : 0.1333911 


s: 69 
logit 69 : -0.4365486 
logit mean 69 : -0.4338391 
logit RMSE 69 : 0.06701286 

boosting 69 : -0.4111775 
boosting mean 69 : -0.48658 
boosting RMSE 69 : 0.1392255 

forest 69 : -0.4284466 
forest mean 69 : -0.3813621 
forest RMSE 69 : 0.06304053 

nnet 69 : -0.2386117 
nnet mean 69 : -0.4245259 
nnet RMSE 69 : 0.1338387 


s: 70 
logit 70 : -0.4038701 
logit mean 70 : -0.433411 
logit RMSE 70 : 0.06653408 

boosting 70 : -0.4409341 
boosting mean 70 : -0.4859279 
boosting RMSE 70 : 0.1383140 

forest 70 : -0.3690932 
forest mean 70 : -0.3811868 
forest RMSE 70 : 0.06269754 

nnet 70 : -0.4322224 
nnet mean 70 : -0.4246358 
nnet RMSE 70 : 0.1329351 


s: 71 
logit 71 : -0.3980519 
logit mean 71 : -0.432913 
logit RMSE 71 : 0.06606427 

boosting 71 : -0.5154441 
boosting mean 71 : -0.4863437 
boosting RMSE 71 : 0.1380182 

forest 71 : -0.3336431 
forest mean 71 : -0.3805172 
forest RMSE 71 : 0.06275056 

nnet 71 : -0.336075 
nnet mean 71 : -0.4233885 
nnet RMSE 71 : 0.1322134 


s: 72 
logit 72 : -0.3996028 
logit mean 72 : -0.4324503 
logit RMSE 72 : 0.0656039 

boosting 72 : -0.4724322 
boosting mean 72 : -0.4861505 
boosting RMSE 72 : 0.137322 

forest 72 : -0.3651246 
forest mean 72 : -0.3803034 
forest RMSE 72 : 0.06244867 

nnet 72 : -0.1481349 
nnet mean 72 : -0.4195655 
nnet RMSE 72 : 0.1346056 


s: 73 
logit 73 : -0.4042026 
logit mean 73 : -0.4320634 
logit RMSE 73 : 0.06515487 

boosting 73 : -0.4057351 
boosting mean 73 : -0.4850489 
boosting RMSE 73 : 0.1363798 

forest 73 : -0.374638 
forest mean 73 : -0.3802258 
forest RMSE 73 : 0.06209046 

nnet 73 : -0.5723666 
nnet mean 73 : -0.4216587 
nnet RMSE 73 : 0.1351941 


s: 74 
logit 74 : -0.4470801 
logit mean 74 : -0.4322663 
logit RMSE 74 : 0.06494415 

boosting 74 : -0.5293215 
boosting mean 74 : -0.4856472 
boosting RMSE 74 : 0.1362869 

forest 74 : -0.4010845 
forest mean 74 : -0.3805076 
forest RMSE 74 : 0.06166963 

nnet 74 : -0.657762 
nnet mean 74 : -0.4248493 
nnet RMSE 74 : 0.1375802 


s: 75 
logit 75 : -0.4069681 
logit mean 75 : -0.431929 
logit RMSE 75 : 0.06451476 

boosting 75 : -0.3245051 
boosting mean 75 : -0.4834986 
boosting RMSE 75 : 0.1356557 

forest 75 : -0.364837 
forest mean 75 : -0.3802987 
forest RMSE 75 : 0.06139154 

nnet 75 : -0.2190495 
nnet mean 75 : -0.4221053 
nnet RMSE 75 : 0.138248 


s: 76 
logit 76 : -0.4591597 
logit mean 76 : -0.4322873 
logit RMSE 76 : 0.06444719 

boosting 76 : -0.5027849 
boosting mean 76 : -0.4837524 
boosting RMSE 76 : 0.1352750 

forest 76 : -0.4047886 
forest mean 76 : -0.3806209 
forest RMSE 76 : 0.06098878 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 76 : -0.2196841 
nnet mean 76 : -0.4194418 
nnet RMSE 76 : 0.1388843 


s: 77 
logit 77 : -0.375665 
logit mean 77 : -0.4315519 
logit RMSE 77 : 0.06408736 

boosting 77 : -0.4421484 
boosting mean 77 : -0.483212 
boosting RMSE 77 : 0.1344795 

forest 77 : -0.4147807 
forest mean 77 : -0.3810646 
forest RMSE 77 : 0.06061486 

nnet 77 : -0.4452791 
nnet mean 77 : -0.4197774 
nnet RMSE 77 : 0.1380759 


s: 78 
logit 78 : -0.3268337 
logit mean 78 : -0.4302094 
logit RMSE 78 : 0.06421188 

boosting 78 : -0.4571574 
boosting mean 78 : -0.482878 
boosting RMSE 78 : 0.1337714 

forest 78 : -0.3406016 
forest mean 78 : -0.3805458 
forest RMSE 78 : 0.06059942 

nnet 78 : -0.2935247 
nnet mean 78 : -0.4181588 
nnet RMSE 78 : 0.1377167 


s: 79 
logit 79 : -0.4213295 
logit mean 79 : -0.430097 
logit RMSE 79 : 0.0638493 

boosting 79 : -0.4773831 
boosting mean 79 : -0.4828085 
boosting RMSE 79 : 0.1332068 

forest 79 : -0.2966823 
forest mean 79 : -0.3794842 
forest RMSE 79 : 0.06132639 

nnet 79 : -0.5244056 
nnet mean 79 : -0.4195037 
nnet RMSE 79 : 0.1375563 


s: 80 
logit 80 : -0.4777804 
logit mean 80 : -0.430693 
logit RMSE 80 : 0.06404214 

boosting 80 : -0.5512568 
boosting mean 80 : -0.4836641 
boosting RMSE 80 : 0.1334475 

forest 80 : -0.28383 
forest mean 80 : -0.3782886 
forest RMSE 80 : 0.06231058 

nnet 80 : -0.5933137 
nnet mean 80 : -0.4216763 
nnet RMSE 80 : 0.1383919 


s: 81 
logit 81 : -0.4820406 
logit mean 81 : -0.4313269 
logit RMSE 81 : 0.06429507 

boosting 81 : -0.4077825 
boosting mean 81 : -0.4827273 
boosting RMSE 81 : 0.1326240 

forest 81 : -0.333022 
forest mean 81 : -0.3777297 
forest RMSE 81 : 0.06237033 

nnet 81 : -0.3107219 
nnet mean 81 : -0.4203065 
nnet RMSE 81 : 0.1378923 


s: 82 
logit 82 : -0.4401704 
logit mean 82 : -0.4314348 
logit RMSE 82 : 0.06405561 

boosting 82 : -0.5687052 
boosting mean 82 : -0.4837758 
boosting RMSE 82 : 0.1331230 

forest 82 : -0.5399093 
forest mean 82 : -0.3797075 
forest RMSE 82 : 0.06388531 

nnet 82 : -0.5508889 
nnet mean 82 : -0.4218989 
nnet RMSE 82 : 0.1380582 


s: 83 
logit 83 : -0.4381745 
logit mean 83 : -0.431516 
logit RMSE 83 : 0.0638063 

boosting 83 : -0.6970899 
boosting mean 83 : -0.4863458 
boosting RMSE 83 : 0.1362777 

forest 83 : -0.4088372 
forest mean 83 : -0.3800585 
forest RMSE 83 : 0.0635067 

nnet 83 : -0.352955 
nnet mean 83 : -0.4210683 
nnet RMSE 83 : 0.1373211 


s: 84 
logit 84 : -0.3995641 
logit mean 84 : -0.4311356 
logit RMSE 84 : 0.06342538 

boosting 84 : -0.4263407 
boosting mean 84 : -0.4856315 
boosting RMSE 84 : 0.1354946 

forest 84 : -0.4261868 
forest mean 84 : -0.3806076 
forest RMSE 84 : 0.06319218 

nnet 84 : -0.5442797 
nnet mean 84 : -0.4225351 
nnet RMSE 84 : 0.137406 


s: 85 
logit 85 : -0.5262137 
logit mean 85 : -0.4322542 
logit RMSE 85 : 0.06452025 

boosting 85 : -0.5191892 
boosting mean 85 : -0.4860263 
boosting RMSE 85 : 0.1353142 

forest 85 : -0.3908891 
forest mean 85 : -0.3807286 
forest RMSE 85 : 0.06282713 

nnet 85 : -0.5229314 
nnet mean 85 : -0.4237162 
nnet RMSE 85 : 0.1372446 


s: 86 
logit 86 : -0.4566919 
logit mean 86 : -0.4325383 
logit RMSE 86 : 0.06443469 

boosting 86 : -0.4646608 
boosting mean 86 : -0.4857778 
boosting RMSE 86 : 0.1347057 

forest 86 : -0.4250454 
forest mean 86 : -0.3812439 
forest RMSE 86 : 0.06251915 

nnet 86 : -0.4080885 
nnet mean 86 : -0.4235345 
nnet RMSE 86 : 0.1364471 


s: 87 
logit 87 : -0.4057558 
logit mean 87 : -0.4322305 
logit RMSE 87 : 0.06406628 

boosting 87 : -0.3164403 
boosting mean 87 : -0.4838314 
boosting RMSE 87 : 0.1342286 

forest 87 : -0.3841365 
forest mean 87 : -0.3812771 
forest RMSE 87 : 0.06218207 

nnet 87 : -0.123689 
nnet mean 87 : -0.420088 
nnet RMSE 87 : 0.1388574 


s: 88 
logit 88 : -0.4497622 
logit mean 88 : -0.4324297 
logit RMSE 88 : 0.06392172 

boosting 88 : -0.5812483 
boosting mean 88 : -0.4849384 
boosting RMSE 88 : 0.1348550 

forest 88 : -0.4841849 
forest mean 88 : -0.3824466 
forest RMSE 88 : 0.06247565 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 88 : -0.2408647 
nnet mean 88 : -0.4180514 
nnet RMSE 88 : 0.1391044 


s: 89 
logit 89 : -0.4905968 
logit mean 89 : -0.4330833 
logit RMSE 89 : 0.06428295 

boosting 89 : -0.567426 
boosting mean 89 : -0.4858653 
boosting RMSE 89 : 0.1352646 

forest 89 : -0.4217913 
forest mean 89 : -0.3828886 
forest RMSE 89 : 0.0621666 

nnet 89 : -0.3758958 
nnet mean 89 : -0.4175777 
nnet RMSE 89 : 0.1383443 


s: 90 
logit 90 : -0.3857128 
logit mean 90 : -0.4325569 
logit RMSE 90 : 0.06394257 

boosting 90 : -0.5154672 
boosting mean 90 : -0.4861942 
boosting RMSE 90 : 0.1350606 

forest 90 : -0.3985472 
forest mean 90 : -0.3830626 
forest RMSE 90 : 0.06182045 

nnet 90 : -0.5089796 
nnet mean 90 : -0.4185933 
nnet RMSE 90 : 0.1380524 


s: 91 
logit 91 : -0.4515017 
logit mean 91 : -0.4327651 
logit RMSE 91 : 0.06381903 

boosting 91 : -0.3787827 
boosting mean 91 : -0.4850138 
boosting RMSE 91 : 0.1343348 

forest 91 : -0.3170925 
forest mean 91 : -0.3823377 
forest RMSE 91 : 0.0620911 

nnet 91 : -0.2975671 
nnet mean 91 : -0.4172633 
nnet RMSE 91 : 0.1377110 


s: 92 
logit 92 : -0.4124325 
logit mean 92 : -0.4325441 
logit RMSE 92 : 0.06348448 

boosting 92 : -0.4032726 
boosting mean 92 : -0.4841253 
boosting RMSE 92 : 0.1336032 

forest 92 : -0.4112741 
forest mean 92 : -0.3826522 
forest RMSE 92 : 0.06176392 

nnet 92 : -0.6371861 
nnet mean 92 : -0.4196538 
nnet RMSE 92 : 0.139175 


s: 93 
logit 93 : -0.5636734 
logit mean 93 : -0.4339541 
logit RMSE 93 : 0.06538345 

boosting 93 : -0.4907843 
boosting mean 93 : -0.4841969 
boosting RMSE 93 : 0.133216 

forest 93 : -0.3925282 
forest mean 93 : -0.3827584 
forest RMSE 93 : 0.06143584 

nnet 93 : -0.3806209 
nnet mean 93 : -0.4192341 
nnet RMSE 93 : 0.1384393 


s: 94 
logit 94 : -0.4774921 
logit mean 94 : -0.4344173 
logit RMSE 94 : 0.06552405 

boosting 94 : -0.6208118 
boosting mean 94 : -0.4856503 
boosting RMSE 94 : 0.1344485 

forest 94 : -0.4665692 
forest mean 94 : -0.38365 
forest RMSE 94 : 0.0614927 

nnet 94 : -0.5140986 
nnet mean 94 : -0.4202433 
nnet RMSE 94 : 0.1382029 


s: 95 
logit 95 : -0.4114287 
logit mean 95 : -0.4341753 
logit RMSE 95 : 0.06518882 

boosting 95 : -0.5173347 
boosting mean 95 : -0.4859838 
boosting RMSE 95 : 0.1342797 

forest 95 : -0.4128444 
forest mean 95 : -0.3839573 
forest RMSE 95 : 0.0611824 

nnet 95 : -0.4280512 
nnet mean 95 : -0.4203255 
nnet RMSE 95 : 0.1375038 


s: 96 
logit 96 : -0.443315 
logit mean 96 : -0.4342705 
logit RMSE 96 : 0.06499892 

boosting 96 : -0.4483465 
boosting mean 96 : -0.4855917 
boosting RMSE 96 : 0.1336696 

forest 96 : -0.3956009 
forest mean 96 : -0.3840786 
forest RMSE 96 : 0.06086456 

nnet 96 : -0.4401526 
nnet mean 96 : -0.420532 
nnet RMSE 96 : 0.1368471 


s: 97 
logit 97 : -0.523415 
logit mean 97 : -0.4351895 
logit RMSE 97 : 0.06586598 

boosting 97 : -0.4772906 
boosting mean 97 : -0.4855062 
boosting RMSE 97 : 0.1332102 

forest 97 : -0.4811434 
forest mean 97 : -0.3850793 
forest RMSE 97 : 0.06110796 

nnet 97 : -0.5159883 
nnet mean 97 : -0.4215161 
nnet RMSE 97 : 0.1366483 


s: 98 
logit 98 : -0.4216358 
logit mean 98 : -0.4350512 
logit RMSE 98 : 0.0655655 

boosting 98 : -0.4874508 
boosting mean 98 : -0.485526 
boosting RMSE 98 : 0.1328229 

forest 98 : -0.3557412 
forest mean 98 : -0.3847799 
forest RMSE 98 : 0.06095955 

nnet 98 : -0.345938 
nnet mean 98 : -0.4207449 
nnet RMSE 98 : 0.1360590 


s: 99 
logit 99 : -0.428376 
logit mean 99 : -0.4349838 
logit RMSE 99 : 0.06529584 

boosting 99 : -0.4591984 
boosting mean 99 : -0.4852601 
boosting RMSE 99 : 0.1322842 

forest 99 : -0.3735812 
forest mean 99 : -0.3846668 
forest RMSE 99 : 0.06070899 

nnet 99 : -0.4860346 
nnet mean 99 : -0.4214044 
nnet RMSE 99 : 0.1356459 


s: 100 
logit 100 : -0.5134946 
logit mean 100 : -0.4357689 
logit RMSE 100 : 0.06595241 

boosting 100 : -0.5176949 
boosting mean 100 : -0.4855844 
boosting RMSE 100 : 0.1321463 

forest 100 : -0.3693048 
forest mean 100 : -0.3845132 
forest RMSE 100 : 0.06048262 

nnet 100 : -0.6340467 
nnet mean 100 : -0.4235308 
nnet RMSE 100 : 0.1369803 


s: 101 
logit 101 : -0.5350441 
logit mean 101 : -0.4367518 
logit RMSE 101 : 0.0669867 

boosting 101 : -0.6434647 
boosting mean 101 : -0.4871476 
boosting RMSE 101 : 0.1337035 

forest 101 : -0.393748 
forest mean 101 : -0.3846046 
forest RMSE 101 : 0.06018567 

nnet 101 : -0.2621382 
nnet mean 101 : -0.4219329 
nnet RMSE 101 : 0.1369890 


s: 102 
logit 102 : -0.4222750 
logit mean 102 : -0.4366099 
logit RMSE 102 : 0.066694 

boosting 102 : -0.6210548 
boosting mean 102 : -0.4884604 
boosting RMSE 102 : 0.1348349 

forest 102 : -0.4011158 
forest mean 102 : -0.3847665 
forest RMSE 102 : 0.05989002 

nnet 102 : -0.5042352 
nnet mean 102 : -0.4227398 
nnet RMSE 102 : 0.1367060 


s: 103 
logit 103 : -0.4844276 
logit mean 103 : -0.4370741 
logit RMSE 103 : 0.06688878 

boosting 103 : -0.7144287 
boosting mean 103 : -0.4906543 
boosting RMSE 103 : 0.1377091 

forest 103 : -0.4426575 
forest mean 103 : -0.3853285 
forest RMSE 103 : 0.05974661 

nnet 103 : -0.4830355 
nnet mean 103 : -0.4233251 
nnet RMSE 103 : 0.1362866 


s: 104 
logit 104 : -0.4043162 
logit mean 104 : -0.4367592 
logit RMSE 104 : 0.06656777 

boosting 104 : -0.2376371 
boosting mean 104 : -0.4882214 
boosting RMSE 104 : 0.1379671 

forest 104 : -0.3347975 
forest mean 104 : -0.3848426 
forest RMSE 104 : 0.05980144 

nnet 104 : -0.5414745 
nnet mean 104 : -0.4244612 
nnet RMSE 104 : 0.1363374 


s: 105 
logit 105 : -0.3440270 
logit mean 105 : -0.435876 
logit RMSE 105 : 0.06647483 

boosting 105 : -0.5547265 
boosting mean 105 : -0.4888548 
boosting RMSE 105 : 0.1381363 

forest 105 : -0.3928429 
forest mean 105 : -0.3849188 
forest RMSE 105 : 0.05952009 

nnet 105 : -0.3747041 
nnet mean 105 : -0.4239873 
nnet RMSE 105 : 0.1357091 


s: 106 
logit 106 : -0.5496408 
logit mean 106 : -0.4369493 
logit RMSE 106 : 0.0677382 

boosting 106 : -0.5101114 
boosting mean 106 : -0.4890553 
boosting RMSE 106 : 0.1378986 

forest 106 : -0.3609164 
forest mean 106 : -0.3846924 
forest RMSE 106 : 0.05936018 

nnet 106 : -0.3375443 
nnet mean 106 : -0.4231718 
nnet RMSE 106 : 0.1352036 


s: 107 
logit 107 : -0.3594672 
logit mean 107 : -0.4362251 
logit RMSE 107 : 0.0675347 

boosting 107 : -0.7238847 
boosting mean 107 : -0.49125 
boosting RMSE 107 : 0.1407788 

forest 107 : -0.3807312 
forest mean 107 : -0.3846554 
forest RMSE 107 : 0.0591115 

nnet 107 : -0.3722522 
nnet mean 107 : -0.4226959 
nnet RMSE 107 : 0.1345971 


s: 108 
logit 108 : -0.4129342 
logit mean 108 : -0.4360095 
logit RMSE 108 : 0.06723283 

boosting 108 : -0.5801005 
boosting mean 108 : -0.4920727 
boosting RMSE 108 : 0.1411932 

forest 108 : -0.3679132 
forest mean 108 : -0.3845003 
forest RMSE 108 : 0.05891816 

nnet 108 : -0.6146916 
nnet mean 108 : -0.4244737 
nnet RMSE 108 : 0.1355559 


s: 109 
logit 109 : -0.5005073 
logit mean 109 : -0.4366012 
logit RMSE 109 : 0.06761257 

boosting 109 : -0.3256615 
boosting mean 109 : -0.490546 
boosting RMSE 109 : 0.1407242 

forest 109 : -0.378572 
forest mean 109 : -0.3844460 
forest RMSE 109 : 0.05868317 

nnet 109 : -0.5969312 
nnet mean 109 : -0.4260559 
nnet RMSE 109 : 0.1362447 


s: 110 
logit 110 : -0.3139270 
logit mean 110 : -0.435486 
logit RMSE 110 : 0.06780303 

boosting 110 : -0.3712667 
boosting mean 110 : -0.4894616 
boosting RMSE 110 : 0.1401099 

forest 110 : -0.3589076 
forest mean 110 : -0.3842138 
forest RMSE 110 : 0.05854706 

nnet 110 : -0.5177394 
nnet mean 110 : -0.4268893 
nnet RMSE 110 : 0.1360878 


s: 111 
logit 111 : -0.4151289 
logit mean 111 : -0.4353026 
logit RMSE 111 : 0.0675122 

boosting 111 : -0.5902348 
boosting mean 111 : -0.4903695 
boosting RMSE 111 : 0.1406413 

forest 111 : -0.3672868 
forest mean 111 : -0.3840613 
forest RMSE 111 : 0.05836539 

nnet 111 : -0.1276279 
nnet mean 111 : -0.4241933 
nnet RMSE 111 : 0.1379181 


s: 112 
logit 112 : -0.364611 
logit mean 112 : -0.4346714 
logit RMSE 112 : 0.06729326 

boosting 112 : -0.543978 
boosting mean 112 : -0.4908481 
boosting RMSE 112 : 0.1406714 

forest 112 : -0.4769549 
forest mean 112 : -0.3848907 
forest RMSE 112 : 0.05855748 

nnet 112 : -0.08899695 
nnet mean 112 : -0.4212005 
nnet RMSE 112 : 0.1404107 


s: 113 
logit 113 : -0.4193462 
logit mean 113 : -0.4345358 
logit RMSE 113 : 0.06701956 

boosting 113 : -0.4106606 
boosting mean 113 : -0.4901385 
boosting RMSE 113 : 0.1400512 

forest 113 : -0.3645477 
forest mean 113 : -0.3847107 
forest RMSE 113 : 0.05839312 

nnet 113 : -0.1047425 
nnet mean 113 : -0.4184000 
nnet RMSE 113 : 0.1425208 


s: 114 
logit 114 : -0.4434924 
logit mean 114 : -0.4346143 
logit RMSE 114 : 0.06684919 

boosting 114 : -0.4619968 
boosting mean 114 : -0.4898917 
boosting RMSE 114 : 0.1395564 

forest 114 : -0.3892288 
forest mean 114 : -0.3847503 
forest RMSE 114 : 0.0581452 

nnet 114 : -0.1847006 
nnet mean 114 : -0.41635 
nnet RMSE 114 : 0.1433199 


s: 115 
logit 115 : -0.3838794 
logit mean 115 : -0.4341732 
logit RMSE 115 : 0.06657488 

boosting 115 : -0.5086525 
boosting mean 115 : -0.4900548 
boosting RMSE 115 : 0.1393172 

forest 115 : -0.3934783 
forest mean 115 : -0.3848262 
forest RMSE 115 : 0.05789504 

nnet 115 : -0.2746194 
nnet mean 115 : -0.4151175 
nnet RMSE 115 : 0.1431736 


s: 116 
logit 116 : -0.3992501 
logit mean 116 : -0.4338721 
logit RMSE 116 : 0.06628733 

boosting 116 : -0.4599191 
boosting mean 116 : -0.489795 
boosting RMSE 116 : 0.1388269 

forest 116 : -0.3972335 
forest mean 116 : -0.3849332 
forest RMSE 116 : 0.05764552 

nnet 116 : -0.5610877 
nnet mean 116 : -0.4163759 
nnet RMSE 116 : 0.1433376 


s: 117 
logit 117 : -0.4499161 
logit mean 117 : -0.4340092 
logit RMSE 117 : 0.06616457 

boosting 117 : -0.4201926 
boosting mean 117 : -0.4892001 
boosting RMSE 117 : 0.138245 

forest 117 : -0.3903885 
forest mean 117 : -0.3849798 
forest RMSE 117 : 0.05740552 

nnet 117 : -0.4206689 
nnet mean 117 : -0.4164126 
nnet RMSE 117 : 0.1427365 


s: 118 
logit 118 : -0.496547 
logit mean 118 : -0.4345392 
logit RMSE 118 : 0.06648041 

boosting 118 : -0.4171966 
boosting mean 118 : -0.4885899 
boosting RMSE 118 : 0.1376671 

forest 118 : -0.3674192 
forest mean 118 : -0.384831 
forest RMSE 118 : 0.0572404 

nnet 118 : -0.2380174 
nnet mean 118 : -0.4149008 
nnet RMSE 118 : 0.1429105 


s: 119 
logit 119 : -0.4296583 
logit mean 119 : -0.4344982 
logit RMSE 119 : 0.0662563 

boosting 119 : -0.4820391 
boosting mean 119 : -0.4885349 
boosting RMSE 119 : 0.1372935 

forest 119 : -0.3732880 
forest mean 119 : -0.384734 
forest RMSE 119 : 0.05705196 

nnet 119 : -0.2748003 
nnet mean 119 : -0.4137234 
nnet RMSE 119 : 0.1427709 


s: 120 
logit 120 : -0.3962745 
logit mean 120 : -0.4341797 
logit RMSE 120 : 0.06598053 

boosting 120 : -0.3554886 
boosting mean 120 : -0.4874261 
boosting RMSE 120 : 0.1367807 

forest 120 : -0.3790561 
forest mean 120 : -0.3846867 
forest RMSE 120 : 0.0568459 

nnet 120 : -0.4676451 
nnet mean 120 : -0.4141728 
nnet RMSE 120 : 0.1423088 


s: 121 
logit 121 : -0.4175251 
logit mean 121 : -0.434042 
logit RMSE 121 : 0.06572663 

boosting 121 : -0.6108473 
boosting mean 121 : -0.4884462 
boosting RMSE 121 : 0.1375563 

forest 121 : -0.3211557 
forest mean 121 : -0.3841616 
forest RMSE 121 : 0.05706247 

nnet 121 : -0.5279365 
nnet mean 121 : -0.415113 
nnet RMSE 121 : 0.1421959 


s: 122 
logit 122 : -0.4072631 
logit mean 122 : -0.4338225 
logit RMSE 122 : 0.06546001 

boosting 122 : -0.4248986 
boosting mean 122 : -0.4879253 
boosting RMSE 122 : 0.1370099 

forest 122 : -0.2979711 
forest mean 122 : -0.3834551 
forest RMSE 122 : 0.05757398 

nnet 122 : -0.3020750 
nnet mean 122 : -0.4141864 
nnet RMSE 122 : 0.1418892 


s: 123 
logit 123 : -0.4817511 
logit mean 123 : -0.4342122 
logit RMSE 123 : 0.06560877 

boosting 123 : -0.5396132 
boosting mean 123 : -0.4883455 
boosting RMSE 123 : 0.1370313 

forest 123 : -0.3221979 
forest mean 123 : -0.3829571 
forest RMSE 123 : 0.057767 

nnet 123 : -0.4203815 
nnet mean 123 : -0.4142368 
nnet RMSE 123 : 0.1413232 


s: 124 
logit 124 : -0.4537582 
logit mean 124 : -0.4343698 
logit RMSE 124 : 0.06552177 

boosting 124 : -0.5501083 
boosting mean 124 : -0.4888436 
boosting RMSE 124 : 0.1371418 

forest 124 : -0.5054604 
forest mean 124 : -0.383945 
forest RMSE 124 : 0.05830787 

nnet 124 : -0.1331122 
nnet mean 124 : -0.4119697 
nnet RMSE 124 : 0.1427782 


s: 125 
logit 125 : -0.4343393 
logit mean 125 : -0.4343696 
logit RMSE 125 : 0.0653314 

boosting 125 : -0.4181631 
boosting mean 125 : -0.4882781 
boosting RMSE 125 : 0.1366017 

forest 125 : -0.3230734 
forest mean 125 : -0.3834581 
forest RMSE 125 : 0.05848035 

nnet 125 : -0.3972337 
nnet mean 125 : -0.4118518 
nnet RMSE 125 : 0.1422061 


s: 126 
logit 126 : -0.3958017 
logit mean 126 : -0.4340635 
logit RMSE 126 : 0.0650727 

boosting 126 : -0.5582132 
boosting mean 126 : -0.4888332 
boosting RMSE 126 : 0.1367867 

forest 126 : -0.3678819 
forest mean 126 : -0.3833344 
forest RMSE 126 : 0.05831806 

nnet 126 : -0.4969319 
nnet mean 126 : -0.412527 
nnet RMSE 126 : 0.1419037 


s: 127 
logit 127 : -0.3030427 
logit mean 127 : -0.4330318 
logit RMSE 127 : 0.06538452 

boosting 127 : -0.4823766 
boosting mean 127 : -0.4887823 
boosting RMSE 127 : 0.1364431 

forest 127 : -0.3169039 
forest mean 127 : -0.3828114 
forest RMSE 127 : 0.05855413 

nnet 127 : -0.2794948 
nnet mean 127 : -0.4114795 
nnet RMSE 127 : 0.1417478 


s: 128 
logit 128 : -0.3465076 
logit mean 128 : -0.4323559 
logit RMSE 128 : 0.06530001 

boosting 128 : -0.6142696 
boosting mean 128 : -0.4897627 
boosting RMSE 128 : 0.1372223 

forest 128 : -0.3868346 
forest mean 128 : -0.3828428 
forest RMSE 128 : 0.05833656 

nnet 128 : -0.3775425 
nnet mean 128 : -0.4112144 
nnet RMSE 128 : 0.141207 


s: 129 
logit 129 : -0.4469212 
logit mean 129 : -0.4324688 
logit RMSE 129 : 0.06517747 

boosting 129 : -0.3818744 
boosting mean 129 : -0.4889264 
boosting RMSE 129 : 0.1366987 

forest 129 : -0.4154406 
forest mean 129 : -0.3830955 
forest RMSE 129 : 0.05812591 

nnet 129 : -0.1418966 
nnet mean 129 : -0.4091267 
nnet RMSE 129 : 0.1424825 


s: 130 
logit 130 : -0.4282693 
logit mean 130 : -0.4324365 
logit RMSE 130 : 0.06497363 

boosting 130 : -0.4159837 
boosting mean 130 : -0.4883653 
boosting RMSE 130 : 0.1361791 

forest 130 : -0.3397271 
forest mean 130 : -0.3827619 
forest RMSE 130 : 0.05814273 

nnet 130 : -0.1666314 
nnet mean 130 : -0.4072613 
nnet RMSE 130 : 0.1434016 


s: 131 
logit 131 : -0.4866952 
logit mean 131 : -0.4328506 
logit RMSE 131 : 0.06516687 

boosting 131 : -0.5412404 
boosting mean 131 : -0.4887689 
boosting RMSE 131 : 0.1362185 

forest 131 : -0.4070862 
forest mean 131 : -0.3829476 
forest RMSE 131 : 0.05792369 

nnet 131 : -0.3826657 
nnet mean 131 : -0.4070736 
nnet RMSE 131 : 0.1428613 


s: 132 
logit 132 : -0.4099047 
logit mean 132 : -0.4326768 
logit RMSE 132 : 0.06492528 

boosting 132 : -0.5112988 
boosting mean 132 : -0.4889396 
boosting RMSE 132 : 0.1360468 

forest 132 : -0.368945 
forest mean 132 : -0.3828415 
forest RMSE 132 : 0.05776714 

nnet 132 : -0.3242557 
nnet mean 132 : -0.4064461 
nnet RMSE 132 : 0.1424717 


s: 133 
logit 133 : -0.4413234 
logit mean 133 : -0.4327418 
logit RMSE 133 : 0.06477992 

boosting 133 : -0.5073832 
boosting mean 133 : -0.4890783 
boosting RMSE 133 : 0.1358539 

forest 133 : -0.3378313 
forest mean 133 : -0.3825031 
forest RMSE 133 : 0.05780149 

nnet 133 : -0.4416347 
nnet mean 133 : -0.4067107 
nnet RMSE 133 : 0.141981 


s: 134 
logit 134 : -0.4121114 
logit mean 134 : -0.4325879 
logit RMSE 134 : 0.06454623 

boosting 134 : -0.5705944 
boosting mean 134 : -0.4896866 
boosting RMSE 134 : 0.1361460 

forest 134 : -0.3286132 
forest mean 134 : -0.3821009 
forest RMSE 134 : 0.05791467 

nnet 134 : -0.4878306 
nnet mean 134 : -0.4073161 
nnet RMSE 134 : 0.1416536 


s: 135 
logit 135 : -0.4283216 
logit mean 135 : -0.4325563 
logit RMSE 135 : 0.0643529 

boosting 135 : -0.4028718 
boosting mean 135 : -0.4890435 
boosting RMSE 135 : 0.1356410 

forest 135 : -0.4776794 
forest mean 135 : -0.3828089 
forest RMSE 135 : 0.0580858 

nnet 135 : -0.3059595 
nnet mean 135 : -0.4065653 
nnet RMSE 135 : 0.1413599 


s: 136 
logit 136 : -0.4460491 
logit mean 136 : -0.4326555 
logit RMSE 136 : 0.06423736 

boosting 136 : -0.450902 
boosting mean 136 : -0.4887631 
boosting RMSE 136 : 0.1352119 

forest 136 : -0.4217379 
forest mean 136 : -0.3830951 
forest RMSE 136 : 0.05790187 

nnet 136 : -0.4175373 
nnet mean 136 : -0.406646 
nnet RMSE 136 : 0.1408472 


s: 137 
logit 137 : -0.3449011 
logit mean 137 : -0.4320149 
logit RMSE 137 : 0.06417537 

boosting 137 : -0.4290334 
boosting mean 137 : -0.4883271 
boosting RMSE 137 : 0.1347403 

forest 137 : -0.3277798 
forest mean 137 : -0.3826914 
forest RMSE 137 : 0.05801919 

nnet 137 : -0.322296 
nnet mean 137 : -0.4060303 
nnet RMSE 137 : 0.1404892 


s: 138 
logit 138 : -0.3014838 
logit mean 138 : -0.4310691 
logit RMSE 138 : 0.06449002 

boosting 138 : -0.725945 
boosting mean 138 : -0.4900489 
boosting RMSE 138 : 0.1370885 

forest 138 : -0.3982364 
forest mean 138 : -0.382804 
forest RMSE 138 : 0.05780879 

nnet 138 : -0.3488987 
nnet mean 138 : -0.4056163 
nnet RMSE 138 : 0.1400468 


s: 139 
logit 139 : -0.4159333 
logit mean 139 : -0.4309602 
logit RMSE 139 : 0.06427183 

boosting 139 : -0.4582086 
boosting mean 139 : -0.4898199 
boosting RMSE 139 : 0.1366837 

forest 139 : -0.363703 
forest mean 139 : -0.3826666 
forest RMSE 139 : 0.05768268 

nnet 139 : -0.2513252 
nnet mean 139 : -0.4045063 
nnet RMSE 139 : 0.1401108 


s: 140 
logit 140 : -0.4346355 
logit mean 140 : -0.4309864 
logit RMSE 140 : 0.06410875 

boosting 140 : -0.3727994 
boosting mean 140 : -0.488984 
boosting RMSE 140 : 0.1362141 

forest 140 : -0.4223587 
forest mean 140 : -0.3829501 
forest RMSE 140 : 0.05750736 

nnet 140 : -0.3389186 
nnet mean 140 : -0.4040378 
nnet RMSE 140 : 0.1397049 


s: 141 
logit 141 : -0.4700062 
logit mean 141 : -0.4312632 
logit RMSE 141 : 0.06415248 

boosting 141 : -0.5319241 
boosting mean 141 : -0.4892886 
boosting RMSE 141 : 0.1361841 

forest 141 : -0.2919867 
forest mean 141 : -0.382305 
forest RMSE 141 : 0.05802056 

nnet 141 : -0.3695367 
nnet mean 141 : -0.4037931 
nnet RMSE 141 : 0.1392323 


s: 142 
logit 142 : -0.4113256 
logit mean 142 : -0.4311228 
logit RMSE 142 : 0.06393326 

boosting 142 : -0.5022361 
boosting mean 142 : -0.4893797 
boosting RMSE 142 : 0.1359747 

forest 142 : -0.3502554 
forest mean 142 : -0.3820793 
forest RMSE 142 : 0.05796641 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 142 : -0.2050634 
nnet mean 142 : -0.4023936 
nnet RMSE 142 : 0.1397022 


s: 143 
logit 143 : -0.5561661 
logit mean 143 : -0.4319972 
logit RMSE 143 : 0.06503401 

boosting 143 : -0.5247262 
boosting mean 143 : -0.4896269 
boosting RMSE 143 : 0.1358992 

forest 143 : -0.3904125 
forest mean 143 : -0.3821376 
forest RMSE 143 : 0.05776894 

nnet 143 : -0.4032652 
nnet mean 143 : -0.4023997 
nnet RMSE 143 : 0.1392132 


s: 144 
logit 144 : -0.5499325 
logit mean 144 : -0.4328162 
logit RMSE 144 : 0.06600122 

boosting 144 : -0.5718255 
boosting mean 144 : -0.4901977 
boosting RMSE 144 : 0.1361814 

forest 144 : -0.3681184 
forest mean 144 : -0.3820402 
forest RMSE 144 : 0.05762928 

nnet 144 : -0.6122986 
nnet mean 144 : -0.4038573 
nnet RMSE 144 : 0.1398525 


s: 145 
logit 145 : -0.4835958 
logit mean 145 : -0.4331664 
logit RMSE 145 : 0.06613859 

boosting 145 : -0.4812005 
boosting mean 145 : -0.4901357 
boosting RMSE 145 : 0.1358784 

forest 145 : -0.4249249 
forest mean 145 : -0.3823360 
forest RMSE 145 : 0.0574675 

nnet 145 : -0.4904703 
nnet mean 145 : -0.4044547 
nnet RMSE 145 : 0.1395717 


s: 146 
logit 146 : -0.4267168 
logit mean 146 : -0.4331222 
logit RMSE 146 : 0.06594878 

boosting 146 : -0.6005652 
boosting mean 146 : -0.4908921 
boosting RMSE 146 : 0.1364259 

forest 146 : -0.2763399 
forest mean 146 : -0.3816100 
forest RMSE 146 : 0.05817759 

nnet 146 : -0.4268365 
nnet mean 146 : -0.404608 
nnet RMSE 146 : 0.1391107 


s: 147 
logit 147 : -0.4657477 
logit mean 147 : -0.4333441 
logit RMSE 147 : 0.06594741 

boosting 147 : -0.6563535 
boosting mean 147 : -0.4920176 
boosting RMSE 147 : 0.1375953 

forest 147 : -0.3877972 
forest mean 147 : -0.3816521 
forest RMSE 147 : 0.05798811 

nnet 147 : -0.3653193 
nnet mean 147 : -0.4043407 
nnet RMSE 147 : 0.1386662 


s: 148 
logit 148 : -0.3792756 
logit mean 148 : -0.4329788 
logit RMSE 148 : 0.06574631 

boosting 148 : -0.4178432 
boosting mean 148 : -0.4915165 
boosting RMSE 148 : 0.1371375 

forest 148 : -0.3454573 
forest mean 148 : -0.3814075 
forest RMSE 148 : 0.05796552 

nnet 148 : -0.297331 
nnet mean 148 : -0.4036177 
nnet RMSE 148 : 0.1384544 


s: 149 
logit 149 : -0.5132283 
logit mean 149 : -0.4335174 
logit RMSE 149 : 0.06617863 

boosting 149 : -0.4650786 
boosting mean 149 : -0.491339 
boosting RMSE 149 : 0.1367805 

forest 149 : -0.3376755 
forest mean 149 : -0.381114 
forest RMSE 149 : 0.05799586 

nnet 149 : -0.5887058 
nnet mean 149 : -0.4048599 
nnet RMSE 149 : 0.1388523 


s: 150 
logit 150 : -0.4292885 
logit mean 150 : -0.4334892 
logit RMSE 150 : 0.066001 

boosting 150 : -0.4905318 
boosting mean 150 : -0.4913337 
boosting RMSE 150 : 0.1365240 

forest 150 : -0.3290862 
forest mean 150 : -0.3807671 
forest RMSE 150 : 0.0580915 

nnet 150 : -0.4393923 
nnet mean 150 : -0.4050901 
nnet RMSE 150 : 0.1384260 


s: 151 
logit 151 : -0.3454936 
logit mean 151 : -0.4329065 
logit RMSE 151 : 0.06593147 

boosting 151 : -0.6602278 
boosting mean 151 : -0.4924522 
boosting RMSE 151 : 0.1377093 

forest 151 : -0.434465 
forest mean 151 : -0.3811228 
forest RMSE 151 : 0.05796671 

nnet 151 : -0.3493726 
nnet mean 151 : -0.4047211 
nnet RMSE 151 : 0.1380284 


s: 152 
logit 152 : -0.4392866 
logit mean 152 : -0.4329484 
logit RMSE 152 : 0.06579145 

boosting 152 : -0.4889051 
boosting mean 152 : -0.4924288 
boosting RMSE 152 : 0.1374448 

forest 152 : -0.4410127 
forest mean 152 : -0.3815168 
forest RMSE 152 : 0.0578714 

nnet 152 : -0.370576 
nnet mean 152 : -0.4044964 
nnet RMSE 152 : 0.1375943 


s: 153 
logit 153 : -0.531876 
logit mean 153 : -0.433595 
logit RMSE 153 : 0.06643713 

boosting 153 : -0.5674685 
boosting mean 153 : -0.4929193 
boosting RMSE 153 : 0.1376623 

forest 153 : -0.4067362 
forest mean 153 : -0.3816816 
forest RMSE 153 : 0.05768454 

nnet 153 : -0.5458517 
nnet mean 153 : -0.4054203 
nnet RMSE 153 : 0.1376499 


s: 154 
logit 154 : -0.3868786 
logit mean 154 : -0.4332917 
logit RMSE 154 : 0.06622952 

boosting 154 : -0.4837859 
boosting mean 154 : -0.49286 
boosting RMSE 154 : 0.1373806 

forest 154 : -0.3221201 
forest mean 154 : -0.3812948 
forest RMSE 154 : 0.05783843 

nnet 154 : -0.4364253 
nnet mean 154 : -0.4056217 
nnet RMSE 154 : 0.1372336 


s: 155 
logit 155 : -0.3450817 
logit mean 155 : -0.4327226 
logit RMSE 155 : 0.06616274 

boosting 155 : -0.4878139 
boosting mean 155 : -0.4928274 
boosting RMSE 155 : 0.1371183 

forest 155 : -0.3455404 
forest mean 155 : -0.3810642 
forest RMSE 155 : 0.05781727 

nnet 155 : -0.3595817 
nnet mean 155 : -0.4053246 
nnet RMSE 155 : 0.1368287 


s: 156 
logit 156 : -0.4868923 
logit mean 156 : -0.4330698 
logit RMSE 156 : 0.06631626 

boosting 156 : -0.3844035 
boosting mean 156 : -0.4921324 
boosting RMSE 156 : 0.1366838 

forest 156 : -0.3491613 
forest mean 156 : -0.3808597 
forest RMSE 156 : 0.05777522 

nnet 156 : -0.5671709 
nnet mean 156 : -0.4063621 
nnet RMSE 156 : 0.1370446 


s: 157 
logit 157 : -0.4994367 
logit mean 157 : -0.4334925 
logit RMSE 157 : 0.06657938 

boosting 157 : -0.6272935 
boosting mean 157 : -0.4929933 
boosting RMSE 157 : 0.1374501 

forest 157 : -0.4051062 
forest mean 157 : -0.3810141 
forest RMSE 157 : 0.05759237 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 157 : -0.1673478 
nnet mean 157 : -0.4048397 
nnet RMSE 157 : 0.1378636 


s: 158 
logit 158 : -0.4491414 
logit mean 158 : -0.4335916 
logit RMSE 158 : 0.06648339 

boosting 158 : -0.4706343 
boosting mean 158 : -0.4928518 
boosting RMSE 158 : 0.1371296 

forest 158 : -0.3844007 
forest mean 158 : -0.3810355 
forest RMSE 158 : 0.05742324 

nnet 158 : -0.3708278 
nnet mean 158 : -0.4046245 
nnet RMSE 158 : 0.1374462 


s: 159 
logit 159 : -0.4429357 
logit mean 159 : -0.4336503 
logit RMSE 159 : 0.06636141 

boosting 159 : -0.4345563 
boosting mean 159 : -0.4924851 
boosting RMSE 159 : 0.1367252 

forest 159 : -0.4005179 
forest mean 159 : -0.3811581 
forest RMSE 159 : 0.05724239 

nnet 159 : -0.5914561 
nnet mean 159 : -0.4057995 
nnet RMSE 159 : 0.1378520 


s: 160 
logit 160 : -0.4387531 
logit mean 160 : -0.4336822 
logit RMSE 160 : 0.06622461 

boosting 160 : -0.5777537 
boosting mean 160 : -0.4930181 
boosting RMSE 160 : 0.1370198 

forest 160 : -0.4129893 
forest mean 160 : -0.381357 
forest RMSE 160 : 0.05707247 

nnet 160 : -0.3383684 
nnet mean 160 : -0.4053781 
nnet RMSE 160 : 0.1375069 


s: 161 
logit 161 : -0.4641347 
logit mean 161 : -0.4338714 
logit RMSE 161 : 0.06621183 

boosting 161 : -0.4365147 
boosting mean 161 : -0.4926671 
boosting RMSE 161 : 0.1366239 

forest 161 : -0.3142906 
forest mean 161 : -0.3809404 
forest RMSE 161 : 0.05729453 

nnet 161 : -0.4235837 
nnet mean 161 : -0.4054911 
nnet RMSE 161 : 0.1370918 


s: 162 
logit 162 : -0.3419857 
logit mean 162 : -0.4333042 
logit RMSE 162 : 0.06616435 

boosting 162 : -0.5951958 
boosting mean 162 : -0.4933 
boosting RMSE 162 : 0.1370622 

forest 162 : -0.3819050 
forest mean 162 : -0.3809464 
forest RMSE 162 : 0.05713511 

nnet 162 : -0.6012977 
nnet mean 162 : -0.4066998 
nnet RMSE 162 : 0.1375801 


s: 163 
logit 163 : -0.4067294 
logit mean 163 : -0.4331412 
logit RMSE 163 : 0.06596318 

boosting 163 : -0.4745781 
boosting mean 163 : -0.4931851 
boosting RMSE 163 : 0.1367659 

forest 163 : -0.4594688 
forest mean 163 : -0.3814281 
forest RMSE 163 : 0.05714972 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 163 : -0.2688165 
nnet mean 163 : -0.4058539 
nnet RMSE 163 : 0.1375418 


s: 164 
logit 164 : -0.3746674 
logit mean 164 : -0.4327846 
logit RMSE 164 : 0.06579151 

boosting 164 : -0.7206108 
boosting mean 164 : -0.4945719 
boosting RMSE 164 : 0.1386277 

forest 164 : -0.2931147 
forest mean 164 : -0.3808896 
forest RMSE 164 : 0.0575833 

nnet 164 : -0.4247153 
nnet mean 164 : -0.4059689 
nnet RMSE 164 : 0.1371354 


s: 165 
logit 165 : -0.3468264 
logit mean 165 : -0.4322636 
logit RMSE 165 : 0.06572234 

boosting 165 : -0.3858382 
boosting mean 165 : -0.4939129 
boosting RMSE 165 : 0.1382114 

forest 165 : -0.4090607 
forest mean 165 : -0.3810604 
forest RMSE 165 : 0.05741287 

nnet 165 : -0.8260217 
nnet mean 165 : -0.4085147 
nnet RMSE 165 : 0.1406844 


s: 166 
logit 166 : -0.53932 
logit mean 166 : -0.4329086 
logit RMSE 166 : 0.06641034 

boosting 166 : -0.3518298 
boosting mean 166 : -0.493057 
boosting RMSE 166 : 0.1378452 

forest 166 : -0.4025608 
forest mean 166 : -0.3811899 
forest RMSE 166 : 0.05724003 

nnet 166 : -0.5828748 
nnet mean 166 : -0.4095651 
nnet RMSE 166 : 0.1409764 


s: 167 
logit 167 : -0.5008882 
logit mean 167 : -0.4333156 
logit RMSE 167 : 0.06666988 

boosting 167 : -0.5495107 
boosting mean 167 : -0.493395 
boosting RMSE 167 : 0.1379180 

forest 167 : -0.4264016 
forest mean 167 : -0.3814606 
forest RMSE 167 : 0.05710495 

nnet 167 : -0.4539687 
nnet mean 167 : -0.4098309 
nnet RMSE 167 : 0.1406157 


s: 168 
logit 168 : -0.4487979 
logit mean 168 : -0.4334078 
logit RMSE 168 : 0.06657769 

boosting 168 : -0.5277985 
boosting mean 168 : -0.4935998 
boosting RMSE 168 : 0.1378599 

forest 168 : -0.3840215 
forest mean 168 : -0.3814759 
forest RMSE 168 : 0.05694808 

nnet 168 : -0.5521669 
nnet mean 168 : -0.4106782 
nnet RMSE 168 : 0.1406872 


s: 169 
logit 169 : -0.4888995 
logit mean 169 : -0.4337361 
logit RMSE 169 : 0.06673174 

boosting 169 : -0.3442728 
boosting mean 169 : -0.4927162 
boosting RMSE 169 : 0.1375183 

forest 169 : -0.4199492 
forest mean 169 : -0.3817035 
forest RMSE 169 : 0.05680008 

nnet 169 : -0.3750873 
nnet mean 169 : -0.4104676 
nnet RMSE 169 : 0.1402835 


s: 170 
logit 170 : -0.4511158 
logit mean 170 : -0.4338384 
logit RMSE 170 : 0.06665058 

boosting 170 : -0.561694 
boosting mean 170 : -0.493122 
boosting RMSE 170 : 0.1376729 

forest 170 : -0.4424477 
forest mean 170 : -0.3820608 
forest RMSE 170 : 0.05672628 

nnet 170 : -0.2832012 
nnet mean 170 : -0.409719 
nnet RMSE 170 : 0.1401568 


s: 171 
logit 171 : -0.3908956 
logit mean 171 : -0.4335872 
logit RMSE 171 : 0.06645905 

boosting 171 : -0.5323302 
boosting mean 171 : -0.4933512 
boosting RMSE 171 : 0.1376423 

forest 171 : -0.3272433 
forest mean 171 : -0.3817403 
forest RMSE 171 : 0.05683317 

nnet 171 : -0.4805699 
nnet mean 171 : -0.4101333 
nnet RMSE 171 : 0.1398822 


s: 172 
logit 172 : -0.4042075 
logit mean 172 : -0.4334164 
logit RMSE 172 : 0.06626635 

boosting 172 : -0.3043314 
boosting mean 172 : -0.4922523 
boosting RMSE 172 : 0.1374353 

forest 172 : -0.4311993 
forest mean 172 : -0.3820278 
forest RMSE 172 : 0.05671762 

nnet 172 : -0.455866 
nnet mean 172 : -0.4103992 
nnet RMSE 172 : 0.1395400 


s: 173 
logit 173 : -0.43032 
logit mean 173 : -0.4333985 
logit RMSE 173 : 0.06611475 

boosting 173 : -0.4629595 
boosting mean 173 : -0.492083 
boosting RMSE 173 : 0.1371211 

forest 173 : -0.3611706 
forest mean 173 : -0.3819072 
forest RMSE 173 : 0.05663046 

nnet 173 : -0.1252021 
nnet mean 173 : -0.4087506 
nnet RMSE 173 : 0.1406959 


s: 174 
logit 174 : -0.4209629 
logit mean 174 : -0.4333271 
logit RMSE 174 : 0.06594365 

boosting 174 : -0.2833009 
boosting mean 174 : -0.4908831 
boosting RMSE 174 : 0.1370124 

forest 174 : -0.3882809 
forest mean 174 : -0.3819439 
forest RMSE 174 : 0.05647449 

nnet 174 : -0.3024969 
nnet mean 174 : -0.40814 
nnet RMSE 174 : 0.1404857 


s: 175 
logit 175 : -0.2850204 
logit mean 175 : -0.4324796 
logit RMSE 175 : 0.06632692 

boosting 175 : -0.2540883 
boosting mean 175 : -0.48953 
boosting RMSE 175 : 0.1370649 

forest 175 : -0.341866 
forest mean 175 : -0.3817149 
forest RMSE 175 : 0.05648411 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 175 : -0.1864642 
nnet mean 175 : -0.4068733 
nnet RMSE 175 : 0.1410106 


s: 176 
logit 176 : -0.511202 
logit mean 176 : -0.4329269 
logit RMSE 176 : 0.06666727 

boosting 176 : -0.3538573 
boosting mean 176 : -0.4887591 
boosting RMSE 176 : 0.1367192 

forest 176 : -0.3408944 
forest mean 176 : -0.3814829 
forest RMSE 176 : 0.05649934 

nnet 176 : -0.5740108 
nnet mean 176 : -0.4078229 
nnet RMSE 176 : 0.1412199 


s: 177 
logit 177 : -0.4590692 
logit mean 177 : -0.4330746 
logit RMSE 177 : 0.06662678 

boosting 177 : -0.6316848 
boosting mean 177 : -0.4895666 
boosting RMSE 177 : 0.1374402 

forest 177 : -0.4467247 
forest mean 177 : -0.3818515 
forest RMSE 177 : 0.05644888 

nnet 177 : -0.4453930 
nnet mean 177 : -0.4080352 
nnet RMSE 177 : 0.1408618 


s: 178 
logit 178 : -0.5291375 
logit mean 178 : -0.4336143 
logit RMSE 178 : 0.06714072 

boosting 178 : -0.7093065 
boosting mean 178 : -0.4908011 
boosting RMSE 178 : 0.1390006 

forest 178 : -0.4093304 
forest mean 178 : -0.3820059 
forest RMSE 178 : 0.05629443 

nnet 178 : -0.5438308 
nnet mean 178 : -0.4087981 
nnet RMSE 178 : 0.1408786 


s: 179 
logit 179 : -0.4810787 
logit mean 179 : -0.4338794 
logit RMSE 179 : 0.06722662 

boosting 179 : -0.3953866 
boosting mean 179 : -0.490268 
boosting RMSE 179 : 0.1386122 

forest 179 : -0.4061229 
forest mean 179 : -0.3821406 
forest RMSE 179 : 0.05613883 

nnet 179 : -0.8854269 
nnet mean 179 : -0.4114608 
nnet RMSE 179 : 0.1450942 


s: 180 
logit 180 : -0.3569563 
logit mean 180 : -0.4334521 
logit RMSE 180 : 0.06711634 

boosting 180 : -0.5313457 
boosting mean 180 : -0.4904962 
boosting RMSE 180 : 0.1385729 

forest 180 : -0.4153459 
forest mean 180 : -0.3823251 
forest RMSE 180 : 0.05599436 

nnet 180 : -0.5310409 
nnet mean 180 : -0.4121251 
nnet RMSE 180 : 0.1450199 


s: 181 
logit 181 : -0.453831 
logit mean 181 : -0.4335647 
logit RMSE 181 : 0.06705017 

boosting 181 : -0.4033224 
boosting mean 181 : -0.4900146 
boosting RMSE 181 : 0.1381897 

forest 181 : -0.4183873 
forest mean 181 : -0.3825243 
forest RMSE 181 : 0.05585618 

nnet 181 : -0.5797572 
nnet mean 181 : -0.4130513 
nnet RMSE 181 : 0.1452346 


s: 182 
logit 182 : -0.3717039 
logit mean 182 : -0.4332248 
logit RMSE 182 : 0.0668986 

boosting 182 : -0.3414197 
boosting mean 182 : -0.4891982 
boosting RMSE 182 : 0.1378780 

forest 182 : -0.3446750 
forest mean 182 : -0.3823164 
forest RMSE 182 : 0.05585328 

nnet 182 : -0.5111799 
nnet mean 182 : -0.4135904 
nnet RMSE 182 : 0.1450694 


s: 183 
logit 183 : -0.4936659 
logit mean 183 : -0.4335550 
logit RMSE 183 : 0.06707391 

boosting 183 : -0.3323741 
boosting mean 183 : -0.4883412 
boosting RMSE 183 : 0.1375916 

forest 183 : -0.3075483 
forest mean 183 : -0.3819078 
forest RMSE 183 : 0.05611817 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 183 : -0.111082 
nnet mean 183 : -0.4119374 
nnet RMSE 183 : 0.1462404 


s: 184 
logit 184 : -0.4931928 
logit mean 184 : -0.4338792 
logit RMSE 184 : 0.06724328 

boosting 184 : -0.6011556 
boosting mean 184 : -0.4889543 
boosting RMSE 184 : 0.1380162 

forest 184 : -0.3462372 
forest mean 184 : -0.3817140 
forest RMSE 184 : 0.05610563 

nnet 184 : -0.4371734 
nnet mean 184 : -0.4120746 
nnet RMSE 184 : 0.1458682 


s: 185 
logit 185 : -0.5181285 
logit mean 185 : -0.4343346 
logit RMSE 185 : 0.06762135 

boosting 185 : -0.5636243 
boosting mean 185 : -0.4893580 
boosting RMSE 185 : 0.1381674 

forest 185 : -0.4448251 
forest mean 185 : -0.3820551 
forest RMSE 185 : 0.05605076 

nnet 185 : -0.2529654 
nnet mean 185 : -0.4112145 
nnet RMSE 185 : 0.1458746 


s: 186 
logit 186 : -0.3920553 
logit mean 186 : -0.4341073 
logit RMSE 186 : 0.06744184 

boosting 186 : -0.722633 
boosting mean 186 : -0.4906121 
boosting RMSE 186 : 0.1398114 

forest 186 : -0.3671537 
forest mean 186 : -0.381975 
forest RMSE 186 : 0.05595174 

nnet 186 : -0.3123266 
nnet mean 186 : -0.4106828 
nnet RMSE 186 : 0.1456239 


s: 187 
logit 187 : -0.4631784 
logit mean 187 : -0.4342627 
logit RMSE 187 : 0.06741976 

boosting 187 : -0.3552129 
boosting mean 187 : -0.4898881 
boosting RMSE 187 : 0.1394755 

forest 187 : -0.5024395 
forest mean 187 : -0.3826192 
forest RMSE 187 : 0.05630251 

nnet 187 : -0.3556144 
nnet mean 187 : -0.4103884 
nnet RMSE 187 : 0.1452702 


s: 188 
logit 188 : -0.4456730 
logit mean 188 : -0.4343234 
logit RMSE 188 : 0.06732267 

boosting 188 : -0.488901 
boosting mean 188 : -0.4898828 
boosting RMSE 188 : 0.1392551 

forest 188 : -0.3084086 
forest mean 188 : -0.3822244 
forest RMSE 188 : 0.05654851 

nnet 188 : -0.3976106 
nnet mean 188 : -0.4103204 
nnet RMSE 188 : 0.1448835 


s: 189 
logit 189 : -0.3987239 
logit mean 189 : -0.4341351 
logit RMSE 189 : 0.0671444 

boosting 189 : -0.4896095 
boosting mean 189 : -0.4898814 
boosting RMSE 189 : 0.1390391 

forest 189 : -0.3698320 
forest mean 189 : -0.3821589 
forest RMSE 189 : 0.05644138 

nnet 189 : -0.4981422 
nnet mean 189 : -0.4107851 
nnet RMSE 189 : 0.1446759 


s: 190 
logit 190 : -0.4942674 
logit mean 190 : -0.4344515 
logit RMSE 190 : 0.06731576 

boosting 190 : -0.6031354 
boosting mean 190 : -0.4904774 
boosting RMSE 190 : 0.1394536 

forest 190 : -0.4576563 
forest mean 190 : -0.3825562 
forest RMSE 190 : 0.05644785 

nnet 190 : -0.442744 
nnet mean 190 : -0.4109533 
nnet RMSE 190 : 0.144328 


s: 191 
logit 191 : -0.3975762 
logit mean 191 : -0.4342585 
logit RMSE 191 : 0.06713954 

boosting 191 : -0.4239596 
boosting mean 191 : -0.4901292 
boosting RMSE 191 : 0.1390988 

forest 191 : -0.3639878 
forest mean 191 : -0.382459 
forest RMSE 191 : 0.05636015 

nnet 191 : -0.5905255 
nnet mean 191 : -0.4118934 
nnet RMSE 191 : 0.1446083 


s: 192 
logit 192 : -0.3900877 
logit mean 192 : -0.4340284 
logit RMSE 192 : 0.06696829 

boosting 192 : -0.5489566 
boosting mean 192 : -0.4904356 
boosting RMSE 192 : 0.1391520 

forest 192 : -0.3533723 
forest mean 192 : -0.3823075 
forest RMSE 192 : 0.05631382 

nnet 192 : -0.5073709 
nnet mean 192 : -0.4123907 
nnet RMSE 192 : 0.1444392 


s: 193 
logit 193 : -0.4579906 
logit mean 193 : -0.4341526 
logit RMSE 193 : 0.06692488 

boosting 193 : -0.5102907 
boosting mean 193 : -0.4905384 
boosting RMSE 193 : 0.1390179 

forest 193 : -0.3625651 
forest mean 193 : -0.3822052 
forest RMSE 193 : 0.05623234 

nnet 193 : -0.1988486 
nnet mean 193 : -0.4112843 
nnet RMSE 193 : 0.1447903 


s: 194 
logit 194 : -0.4201369 
logit mean 194 : -0.4340803 
logit RMSE 194 : 0.06676782 

boosting 194 : -0.5413645 
boosting mean 194 : -0.4908004 
boosting RMSE 194 : 0.1390301 

forest 194 : -0.3705142 
forest mean 194 : -0.3821450 
forest RMSE 194 : 0.05612716 

nnet 194 : -0.2539406 
nnet mean 194 : -0.4104732 
nnet RMSE 194 : 0.1447969 


s: 195 
logit 195 : -0.514544 
logit mean 195 : -0.434493 
logit RMSE 195 : 0.06709966 

boosting 195 : -0.554734 
boosting mean 195 : -0.4911283 
boosting RMSE 195 : 0.1391151 

forest 195 : -0.3231306 
forest mean 195 : -0.3818423 
forest RMSE 195 : 0.05625305 

nnet 195 : -0.6399086 
nnet mean 195 : -0.4116498 
nnet RMSE 195 : 0.1454434 


s: 196 
logit 196 : -0.4837891 
logit mean 196 : -0.4347445 
logit RMSE 196 : 0.06719533 

boosting 196 : -0.6257341 
boosting mean 196 : -0.4918151 
boosting RMSE 196 : 0.1396934 

forest 196 : -0.4016481 
forest mean 196 : -0.3819434 
forest RMSE 196 : 0.05610948 

nnet 196 : -0.5456161 
nnet mean 196 : -0.4123333 
nnet RMSE 196 : 0.1454443 


s: 197 
logit 197 : -0.4469424 
logit mean 197 : -0.4348064 
logit RMSE 197 : 0.06710796 

boosting 197 : -0.5841883 
boosting mean 197 : -0.492284 
boosting RMSE 197 : 0.1399550 

forest 197 : -0.3754407 
forest mean 197 : -0.3819104 
forest RMSE 197 : 0.05599424 

nnet 197 : -0.4929376 
nnet mean 197 : -0.4127425 
nnet RMSE 197 : 0.1452257 


s: 198 
logit 198 : -0.4459302 
logit mean 198 : -0.4348626 
logit RMSE 198 : 0.06701782 

boosting 198 : -0.5367659 
boosting mean 198 : -0.4925086 
boosting RMSE 198 : 0.1399391 

forest 198 : -0.4128451 
forest mean 198 : -0.3820666 
forest RMSE 198 : 0.05586012 

nnet 198 : -0.4548482 
nnet mean 198 : -0.4129551 
nnet RMSE 198 : 0.1449109 


s: 199 
logit 199 : -0.4433568 
logit mean 199 : -0.4349053 
logit RMSE 199 : 0.06691984 

boosting 199 : -0.4162583 
boosting mean 199 : -0.4921254 
boosting RMSE 199 : 0.1395918 

forest 199 : -0.4924964 
forest mean 199 : -0.3826215 
forest RMSE 199 : 0.05610406 

nnet 199 : -0.5079433 
nnet mean 199 : -0.4134325 
nnet RMSE 199 : 0.1447488 


s: 200 
logit 200 : -0.4941832 
logit mean 200 : -0.4352016 
logit RMSE 200 : 0.06708372 

boosting 200 : -0.4717784 
boosting mean 200 : -0.4920237 
boosting RMSE 200 : 0.1393349 

forest 200 : -0.3981838 
forest mean 200 : -0.3826993 
forest RMSE 200 : 0.05596377 

nnet 200 : -0.4222283 
nnet mean 200 : -0.4134764 
nnet RMSE 200 : 0.144395 


s: 201 
logit 201 : -0.4894516 
logit mean 201 : -0.4354716 
logit RMSE 201 : 0.06721343 

boosting 201 : -0.3004714 
boosting mean 201 : -0.4910707 
boosting RMSE 201 : 0.1391650 

forest 201 : -0.2755256 
forest mean 201 : -0.3821661 
forest RMSE 201 : 0.05651058 

nnet 201 : -0.3416994 
nnet mean 201 : -0.4131193 
nnet RMSE 201 : 0.1440941 


s: 202 
logit 202 : -0.4405905 
logit mean 202 : -0.4354969 
logit RMSE 202 : 0.06710765 

boosting 202 : -0.5009104 
boosting mean 202 : -0.4911194 
boosting RMSE 202 : 0.1390016 

forest 202 : -0.3618685 
forest mean 202 : -0.3820656 
forest RMSE 202 : 0.05643434 

nnet 202 : -0.4335603 
nnet mean 202 : -0.4132205 
nnet RMSE 202 : 0.1437563 


s: 203 
logit 203 : -0.4411835 
logit mean 203 : -0.4355249 
logit RMSE 203 : 0.06700454 

boosting 203 : -0.3571243 
boosting mean 203 : -0.4904594 
boosting RMSE 203 : 0.1386914 

forest 203 : -0.4999154 
forest mean 203 : -0.3826462 
forest RMSE 203 : 0.05673027 

nnet 203 : -0.3399632 
nnet mean 203 : -0.4128597 
nnet RMSE 203 : 0.1434637 


s: 204 
logit 204 : -0.4845294 
logit mean 204 : -0.4357651 
logit RMSE 204 : 0.0671016 

boosting 204 : -0.4160969 
boosting mean 204 : -0.4900948 
boosting RMSE 204 : 0.1383557 

forest 204 : -0.3184929 
forest mean 204 : -0.3823317 
forest RMSE 204 : 0.05687806 

nnet 204 : -0.3671319 
nnet mean 204 : -0.4126355 
nnet RMSE 204 : 0.1431302 


s: 205 
logit 205 : -0.454799 
logit mean 205 : -0.435858 
logit RMSE 205 : 0.06704707 

boosting 205 : -0.3657633 
boosting mean 205 : -0.4894883 
boosting RMSE 205 : 0.1380385 

forest 205 : -0.4288058 
forest mean 205 : -0.3825584 
forest RMSE 205 : 0.05677482 

nnet 205 : -0.3563904 
nnet mean 205 : -0.4123611 
nnet RMSE 205 : 0.1428131 


s: 206 
logit 206 : -0.4042658 
logit mean 206 : -0.4357046 
logit RMSE 206 : 0.0668848 

boosting 206 : -0.700646 
boosting mean 206 : -0.4905134 
boosting RMSE 206 : 0.1392872 

forest 206 : -0.3487991 
forest mean 206 : -0.3823945 
forest RMSE 206 : 0.05674908 

nnet 206 : -0.8074653 
nnet mean 206 : -0.4142791 
nnet RMSE 206 : 0.1452671 


s: 207 
logit 207 : -0.4039946 
logit mean 207 : -0.4355514 
logit RMSE 207 : 0.06672362 

boosting 207 : -0.3137864 
boosting mean 207 : -0.4896596 
boosting RMSE 207 : 0.1390795 

forest 207 : -0.3502355 
forest mean 207 : -0.3822392 
forest RMSE 207 : 0.05671741 

nnet 207 : -0.4867391 
nnet mean 207 : -0.4146292 
nnet RMSE 207 : 0.1450412 


s: 208 
logit 208 : -0.4585732 
logit mean 208 : -0.4356621 
logit RMSE 208 : 0.06668682 

boosting 208 : -0.528578 
boosting mean 208 : -0.4898467 
boosting RMSE 208 : 0.1390309 

forest 208 : -0.3599775 
forest mean 208 : -0.3821321 
forest RMSE 208 : 0.05664892 

nnet 208 : -0.5705637 
nnet mean 208 : -0.4153789 
nnet RMSE 208 : 0.1451746 


s: 209 
logit 209 : -0.438946 
logit mean 209 : -0.4356778 
logit RMSE 209 : 0.06658162 

boosting 209 : -0.3933593 
boosting mean 209 : -0.4893851 
boosting RMSE 209 : 0.1386986 

forest 209 : -0.4480639 
forest mean 209 : -0.3824476 
forest RMSE 209 : 0.05661094 

nnet 209 : -0.443622 
nnet mean 209 : -0.415514 
nnet RMSE 209 : 0.1448583 


s: 210 
logit 210 : -0.6644818 
logit mean 210 : -0.4367674 
logit RMSE 210 : 0.06888468 

boosting 210 : -0.5260638 
boosting mean 210 : -0.4895597 
boosting RMSE 210 : 0.1386412 

forest 210 : -0.4618541 
forest mean 210 : -0.3828257 
forest RMSE 210 : 0.05663706 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 210 : -0.293658 
nnet mean 210 : -0.4149337 
nnet RMSE 210 : 0.1446992 


s: 211 
logit 211 : -0.3825134 
logit mean 211 : -0.4365102 
logit RMSE 211 : 0.0687318 

boosting 211 : -0.3227129 
boosting mean 211 : -0.488769 
boosting RMSE 211 : 0.1384146 

forest 211 : -0.3815669 
forest mean 211 : -0.3828198 
forest RMSE 211 : 0.05651693 

nnet 211 : -0.3318336 
nnet mean 211 : -0.4145399 
nnet RMSE 211 : 0.1444322 


s: 212 
logit 212 : -0.5126065 
logit mean 212 : -0.4368692 
logit RMSE 212 : 0.06900427 

boosting 212 : -0.341999 
boosting mean 212 : -0.4880767 
boosting RMSE 212 : 0.1381452 

forest 212 : -0.3524395 
forest mean 212 : -0.3826765 
forest RMSE 212 : 0.05647802 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 212 : -0.2777891 
nnet mean 212 : -0.4138948 
nnet RMSE 212 : 0.1443354 


s: 213 
logit 213 : -0.5132 
logit mean 213 : -0.4372275 
logit RMSE 213 : 0.06927767 

boosting 213 : -0.5753876 
boosting mean 213 : -0.4884866 
boosting RMSE 213 : 0.1383434 

forest 213 : -0.449662 
forest mean 213 : -0.3829910 
forest RMSE 213 : 0.05644794 

nnet 213 : -0.2600219 
nnet mean 213 : -0.4131724 
nnet RMSE 213 : 0.1443152 


s: 214 
logit 214 : -0.558304 
logit mean 214 : -0.4377933 
logit RMSE 214 : 0.06995764 

boosting 214 : -0.5350606 
boosting mean 214 : -0.4887042 
boosting RMSE 214 : 0.1383283 

forest 214 : -0.4394071 
forest mean 214 : -0.3832546 
forest RMSE 214 : 0.05638029 

nnet 214 : -0.4064316 
nnet mean 214 : -0.4131409 
nnet RMSE 214 : 0.1439783 


s: 215 
logit 215 : -0.3235541 
logit mean 215 : -0.437262 
logit RMSE 215 : 0.06998921 

boosting 215 : -0.3274766 
boosting mean 215 : -0.4879543 
boosting RMSE 215 : 0.1380948 

forest 215 : -0.2537262 
forest mean 215 : -0.3826521 
forest RMSE 215 : 0.05712678 

nnet 215 : -0.3737481 
nnet mean 215 : -0.4129577 
nnet RMSE 215 : 0.1436543 


s: 216 
logit 216 : -0.4813742 
logit mean 216 : -0.4374662 
logit RMSE 216 : 0.07004618 

boosting 216 : -0.5560097 
boosting mean 216 : -0.4882694 
boosting RMSE 216 : 0.1381831 

forest 216 : -0.4406487 
forest mean 216 : -0.3829206 
forest RMSE 216 : 0.05706146 

nnet 216 : -0.4558392 
nnet mean 216 : -0.4131562 
nnet RMSE 216 : 0.1433717 


s: 217 
logit 217 : -0.5310807 
logit mean 217 : -0.4378976 
logit RMSE 217 : 0.07044883 

boosting 217 : -0.6518689 
boosting mean 217 : -0.4890233 
boosting RMSE 217 : 0.1389205 

forest 217 : -0.4168192 
forest mean 217 : -0.3830768 
forest RMSE 217 : 0.05694128 

nnet 217 : -0.2631045 
nnet mean 217 : -0.4124647 
nnet RMSE 217 : 0.1433425 


s: 218 
logit 218 : -0.3632210 
logit mean 218 : -0.437555 
logit RMSE 218 : 0.07033119 

boosting 218 : -0.4207846 
boosting mean 218 : -0.4887103 
boosting RMSE 218 : 0.1386087 

forest 218 : -0.4244108 
forest mean 218 : -0.3832664 
forest RMSE 218 : 0.05683458 

nnet 218 : -0.5792219 
nnet mean 218 : -0.4132297 
nnet RMSE 218 : 0.1435276 


s: 219 
logit 219 : -0.4618872 
logit mean 219 : -0.4376661 
logit RMSE 219 : 0.07029494 

boosting 219 : -0.3296885 
boosting mean 219 : -0.4879842 
boosting RMSE 219 : 0.1383735 

forest 219 : -0.4084502 
forest mean 219 : -0.3833814 
forest RMSE 219 : 0.05670755 

nnet 219 : -0.2449246 
nnet mean 219 : -0.4124612 
nnet RMSE 219 : 0.1435824 


s: 220 
logit 220 : -0.4419218 
logit mean 220 : -0.4376855 
logit RMSE 220 : 0.07019192 

boosting 220 : -0.4624015 
boosting mean 220 : -0.4878679 
boosting RMSE 220 : 0.1381227 

forest 220 : -0.2959951 
forest mean 220 : -0.3829842 
forest RMSE 220 : 0.05701138 

nnet 220 : -0.432392 
nnet mean 220 : -0.4125518 
nnet RMSE 220 : 0.1432724 


s: 221 
logit 221 : -0.4891696 
logit mean 221 : -0.4379185 
logit RMSE 221 : 0.07028934 

boosting 221 : -0.5958085 
boosting mean 221 : -0.4883563 
boosting RMSE 221 : 0.1384379 

forest 221 : -0.2990066 
forest mean 221 : -0.3826042 
forest RMSE 221 : 0.05728649 

nnet 221 : -0.6530993 
nnet mean 221 : -0.4136402 
nnet RMSE 221 : 0.1439582 


s: 222 
logit 222 : -0.4982559 
logit mean 222 : -0.4381902 
logit RMSE 222 : 0.07044021 

boosting 222 : -0.5275818 
boosting mean 222 : -0.488533 
boosting RMSE 222 : 0.1383909 

forest 222 : -0.3292083 
forest mean 222 : -0.3823637 
forest RMSE 222 : 0.05735446 

nnet 222 : -0.3490071 
nnet mean 222 : -0.4133491 
nnet RMSE 222 : 0.1436743 


s: 223 
logit 223 : -0.4312821 
logit mean 223 : -0.4381593 
logit RMSE 223 : 0.07031331 

boosting 223 : -0.5287409 
boosting mean 223 : -0.4887133 
boosting RMSE 223 : 0.1383491 

forest 223 : -0.4404619 
forest mean 223 : -0.3826242 
forest RMSE 223 : 0.05728982 

nnet 223 : -0.3526172 
nnet mean 223 : -0.4130767 
nnet RMSE 223 : 0.1433869 


s: 224 
logit 224 : -0.3801809 
logit mean 224 : -0.4379004 
logit RMSE 224 : 0.07016868 

boosting 224 : -0.5089738 
boosting mean 224 : -0.4888037 
boosting RMSE 224 : 0.1382319 

forest 224 : -0.3601474 
forest mean 224 : -0.3825239 
forest RMSE 224 : 0.05722379 

nnet 224 : -0.2238592 
nnet mean 224 : -0.412232 
nnet RMSE 224 : 0.1435498 


s: 225 
logit 225 : -0.4733187 
logit mean 225 : -0.4380578 
logit RMSE 225 : 0.07018299 

boosting 225 : -0.5307564 
boosting mean 225 : -0.4889902 
boosting RMSE 225 : 0.1381995 

forest 225 : -0.4193839 
forest mean 225 : -0.3826877 
forest RMSE 225 : 0.0571111 

nnet 225 : -0.510378 
nnet mean 225 : -0.4126682 
nnet RMSE 225 : 0.1434193 


s: 226 
logit 226 : -0.5043401 
logit mean 226 : -0.4383511 
logit RMSE 226 : 0.07037066 

boosting 226 : -0.5367194 
boosting mean 226 : -0.4892014 
boosting RMSE 226 : 0.1381930 

forest 226 : -0.4412116 
forest mean 226 : -0.3829467 
forest RMSE 226 : 0.05705051 

nnet 226 : -0.6258853 
nnet mean 226 : -0.4136117 
nnet RMSE 226 : 0.1438883 


s: 227 
logit 227 : -0.4432415 
logit mean 227 : -0.4383727 
logit RMSE 227 : 0.07027412 

boosting 227 : -0.429664 
boosting mean 227 : -0.4889391 
boosting RMSE 227 : 0.1379023 

forest 227 : -0.390547 
forest mean 227 : -0.3829802 
forest RMSE 227 : 0.05692817 

nnet 227 : -0.3283519 
nnet mean 227 : -0.4132361 
nnet RMSE 227 : 0.1436498 


s: 228 
logit 228 : -0.4443019 
logit mean 228 : -0.4383987 
logit RMSE 228 : 0.07018119 

boosting 228 : -0.4647622 
boosting mean 228 : -0.4888331 
boosting RMSE 228 : 0.1376664 

forest 228 : -0.3773951 
forest mean 228 : -0.3829557 
forest RMSE 228 : 0.05682291 

nnet 228 : -0.4395337 
nnet mean 228 : -0.4133514 
nnet RMSE 228 : 0.1433583 


s: 229 
logit 229 : -0.4177555 
logit mean 229 : -0.4383085 
logit RMSE 229 : 0.07003762 

boosting 229 : -0.3861995 
boosting mean 229 : -0.4883849 
boosting RMSE 229 : 0.1373685 

forest 229 : -0.4629008 
forest mean 229 : -0.3833048 
forest RMSE 229 : 0.05685087 

nnet 229 : -0.1173594 
nnet mean 229 : -0.4120589 
nnet RMSE 229 : 0.1442592 


s: 230 
logit 230 : -0.4459403 
logit mean 230 : -0.4383417 
logit RMSE 230 : 0.06995082 

boosting 230 : -0.4508444 
boosting mean 230 : -0.4882217 
boosting RMSE 230 : 0.1371106 

forest 230 : -0.3072156 
forest mean 230 : -0.3829739 
forest RMSE 230 : 0.0570561 

nnet 230 : -0.4728607 
nnet mean 230 : -0.4123232 
nnet RMSE 230 : 0.1440254 


s: 231 
logit 231 : -0.4866713 
logit mean 231 : -0.4385509 
logit RMSE 231 : 0.0700318 

boosting 231 : -0.4796692 
boosting mean 231 : -0.4881846 
boosting RMSE 231 : 0.1369139 

forest 231 : -0.4421368 
forest mean 231 : -0.3832301 
forest RMSE 231 : 0.05699994 

nnet 231 : -0.3261030 
nnet mean 231 : -0.41195 
nnet RMSE 231 : 0.1437955 


s: 232 
logit 232 : -0.3766465 
logit mean 232 : -0.4382841 
logit RMSE 232 : 0.06989753 

boosting 232 : -0.5734837 
boosting mean 232 : -0.4885523 
boosting RMSE 232 : 0.1370924 

forest 232 : -0.2987192 
forest mean 232 : -0.3828658 
forest RMSE 232 : 0.05726433 

nnet 232 : -0.4192768 
nnet mean 232 : -0.4119815 
nnet RMSE 232 : 0.1434909 


s: 233 
logit 233 : -0.4504694 
logit mean 233 : -0.4383364 
logit RMSE 233 : 0.0698257 

boosting 233 : -0.5845671 
boosting mean 233 : -0.4889644 
boosting RMSE 233 : 0.1373313 

forest 233 : -0.3692104 
forest mean 233 : -0.3828072 
forest RMSE 233 : 0.0571769 

nnet 233 : -0.4785489 
nnet mean 233 : -0.4122672 
nnet RMSE 233 : 0.1432751 


s: 234 
logit 234 : -0.4404698 
logit mean 234 : -0.4383455 
logit RMSE 234 : 0.06972655 

boosting 234 : -0.4293672 
boosting mean 234 : -0.4887097 
boosting RMSE 234 : 0.1370509 

forest 234 : -0.3594257 
forest mean 234 : -0.3827073 
forest RMSE 234 : 0.05711622 

nnet 234 : -0.7331299 
nnet mean 234 : -0.4136385 
nnet RMSE 234 : 0.1446177 


s: 235 
logit 235 : -0.5174549 
logit mean 235 : -0.4386822 
logit RMSE 235 : 0.06999863 

boosting 235 : -0.327801 
boosting mean 235 : -0.488025 
boosting RMSE 235 : 0.1368401 

forest 235 : -0.3908484 
forest mean 235 : -0.3827419 
forest RMSE 235 : 0.05699769 

nnet 235 : -0.4167341 
nnet mean 235 : -0.4136516 
nnet RMSE 235 : 0.1443138 


s: 236 
logit 236 : -0.4800938 
logit mean 236 : -0.4388576 
logit RMSE 236 : 0.07004447 

boosting 236 : -0.01744280 
boosting mean 236 : -0.486031 
boosting RMSE 236 : 0.138802 

forest 236 : -0.3537679 
forest mean 236 : -0.3826191 
forest RMSE 236 : 0.05695637 

nnet 236 : -0.3233694 
nnet mean 236 : -0.4132691 
nnet RMSE 236 : 0.1440941 


s: 237 
logit 237 : -0.4550447 
logit mean 237 : -0.4389259 
logit RMSE 237 : 0.06998794 

boosting 237 : -0.4092745 
boosting mean 237 : -0.4857071 
boosting RMSE 237 : 0.1385102 

forest 237 : -0.4616375 
forest mean 237 : -0.3829525 
forest RMSE 237 : 0.05697693 

nnet 237 : -0.3514093 
nnet mean 237 : -0.4130081 
nnet RMSE 237 : 0.1438244 


s: 238 
logit 238 : -0.4354545 
logit mean 238 : -0.4389113 
logit RMSE 238 : 0.06987855 

boosting 238 : -0.3732219 
boosting mean 238 : -0.4852345 
boosting RMSE 238 : 0.1382298 

forest 238 : -0.3287696 
forest mean 238 : -0.3827249 
forest RMSE 238 : 0.05704427 

nnet 238 : -0.4856248 
nnet mean 238 : -0.4133132 
nnet RMSE 238 : 0.1436292 


s: 239 
logit 239 : -0.4378873 
logit mean 239 : -0.4389071 
logit RMSE 239 : 0.06977526 

boosting 239 : -0.5639213 
boosting mean 239 : -0.4855637 
boosting RMSE 239 : 0.1383472 

forest 239 : -0.3232601 
forest mean 239 : -0.3824761 
forest RMSE 239 : 0.05714082 

nnet 239 : -0.2494969 
nnet mean 239 : -0.4126278 
nnet RMSE 239 : 0.1436587 


s: 240 
logit 240 : -0.4629252 
logit mean 240 : -0.4390071 
logit RMSE 240 : 0.06974811 

boosting 240 : -0.7127823 
boosting mean 240 : -0.4865105 
boosting RMSE 240 : 0.1395272 

forest 240 : -0.4187066 
forest mean 240 : -0.3826270 
forest RMSE 240 : 0.05703444 

nnet 240 : -0.3280839 
nnet mean 240 : -0.4122755 
nnet RMSE 240 : 0.1434342 


s: 241 
logit 241 : -0.4307222 
logit mean 241 : -0.4389728 
logit RMSE 241 : 0.06963138 

boosting 241 : -0.5055742 
boosting mean 241 : -0.4865896 
boosting RMSE 241 : 0.1394034 

forest 241 : -0.4125432 
forest mean 241 : -0.3827512 
forest RMSE 241 : 0.05692172 

nnet 241 : -0.3086315 
nnet mean 241 : -0.4118454 
nnet RMSE 241 : 0.1432573 


s: 242 
logit 242 : -0.4354753 
logit mean 242 : -0.4389583 
logit RMSE 242 : 0.06952478 

boosting 242 : -0.4489684 
boosting mean 242 : -0.4864341 
boosting RMSE 242 : 0.1391507 

forest 242 : -0.4059537 
forest mean 242 : -0.3828471 
forest RMSE 242 : 0.05680528 

nnet 242 : -0.4469303 
nnet mean 242 : -0.4119904 
nnet RMSE 242 : 0.1429928 


s: 243 
logit 243 : -0.4069054 
logit mean 243 : -0.4388264 
logit RMSE 243 : 0.06938299 

boosting 243 : -0.6483502 
boosting mean 243 : -0.4871004 
boosting RMSE 243 : 0.139775 

forest 243 : -0.3448059 
forest mean 243 : -0.3826905 
forest RMSE 243 : 0.05679874 

nnet 243 : -0.4014701 
nnet mean 243 : -0.4119471 
nnet RMSE 243 : 0.1426983 


s: 244 
logit 244 : -0.48617 
logit mean 244 : -0.4390204 
logit RMSE 244 : 0.06946007 

boosting 244 : -0.4184668 
boosting mean 244 : -0.4868192 
boosting RMSE 244 : 0.1394933 

forest 244 : -0.3497929 
forest mean 244 : -0.3825557 
forest RMSE 244 : 0.05677329 

nnet 244 : -0.3438899 
nnet mean 244 : -0.4116682 
nnet RMSE 244 : 0.1424509 


s: 245 
logit 245 : -0.3323861 
logit mean 245 : -0.4385852 
logit RMSE 245 : 0.06945263 

boosting 245 : -0.482941 
boosting mean 245 : -0.4868033 
boosting RMSE 245 : 0.1393091 

forest 245 : -0.3890447 
forest mean 245 : -0.3825822 
forest RMSE 245 : 0.05666163 

nnet 245 : -0.7725103 
nnet mean 245 : -0.413141 
nnet RMSE 245 : 0.1441382 


s: 246 
logit 246 : -0.4615658 
logit mean 246 : -0.4386786 
logit RMSE 246 : 0.06942239 

boosting 246 : -0.5617499 
boosting mean 246 : -0.487108 
boosting RMSE 246 : 0.1394077 

forest 246 : -0.3694486 
forest mean 246 : -0.3825288 
forest RMSE 246 : 0.05657989 

nnet 246 : -0.1827404 
nnet mean 246 : -0.4122044 
nnet RMSE 246 : 0.1445103 


s: 247 
logit 247 : -0.4235843 
logit mean 247 : -0.4386175 
logit RMSE 247 : 0.06929796 

boosting 247 : -0.5052254 
boosting mean 247 : -0.4871813 
boosting RMSE 247 : 0.1392862 

forest 247 : -0.3635527 
forest mean 247 : -0.3824520 
forest RMSE 247 : 0.05651284 

nnet 247 : -0.2089135 
nnet mean 247 : -0.4113814 
nnet RMSE 247 : 0.1447291 


s: 248 
logit 248 : -0.4763476 
logit mean 248 : -0.4387696 
logit RMSE 248 : 0.06932783 

boosting 248 : -0.5597107 
boosting mean 248 : -0.4874738 
boosting RMSE 248 : 0.1393746 

forest 248 : -0.3961744 
forest mean 248 : -0.3825073 
forest RMSE 248 : 0.05639931 

nnet 248 : -0.3927474 
nnet mean 248 : -0.4113063 
nnet RMSE 248 : 0.1444378 


s: 249 
logit 249 : -0.4437636 
logit mean 249 : -0.4387897 
logit RMSE 249 : 0.06924404 

boosting 249 : -0.5827848 
boosting mean 249 : -0.4878566 
boosting RMSE 249 : 0.1395759 

forest 249 : -0.3869283 
forest mean 249 : -0.3825250 
forest RMSE 249 : 0.05629204 

nnet 249 : -0.4788999 
nnet mean 249 : -0.4115777 
nnet RMSE 249 : 0.1442341 


s: 250 
logit 250 : -0.5969994 
logit mean 250 : -0.4394225 
logit RMSE 250 : 0.0702196 

boosting 250 : -0.4979523 
boosting mean 250 : -0.487897 
boosting RMSE 250 : 0.1394342 

forest 250 : -0.4611468 
forest mean 250 : -0.3828395 
forest RMSE 250 : 0.05631229 

nnet 250 : -0.3278393 
nnet mean 250 : -0.4112428 
nnet RMSE 250 : 0.1440177 


s: 251 
logit 251 : -0.3493005 
logit mean 251 : -0.4390635 
logit RMSE 251 : 0.07015261 

boosting 251 : -0.544078 
boosting mean 251 : -0.4881208 
boosting RMSE 251 : 0.1394530 

forest 251 : -0.3150367 
forest mean 251 : -0.3825694 
forest RMSE 251 : 0.0564553 

nnet 251 : -0.454396 
nnet mean 251 : -0.4114147 
nnet RMSE 251 : 0.1437715 


s: 252 
logit 252 : -0.3820237 
logit mean 252 : -0.4388371 
logit RMSE 252 : 0.07002244 

boosting 252 : -0.5050852 
boosting mean 252 : -0.4881881 
boosting RMSE 252 : 0.1393333 

forest 252 : -0.3632677 
forest mean 252 : -0.3824928 
forest RMSE 252 : 0.05639067 

nnet 252 : -0.3942594 
nnet mean 252 : -0.4113466 
nnet RMSE 252 : 0.1434864 


s: 253 
logit 253 : -0.4620993 
logit mean 253 : -0.4389291 
logit RMSE 253 : 0.06999289 

boosting 253 : -0.6838478 
boosting mean 253 : -0.4889615 
boosting RMSE 253 : 0.1401981 

forest 253 : -0.3801533 
forest mean 253 : -0.3824836 
forest RMSE 253 : 0.05629294 

nnet 253 : -0.4396597 
nnet mean 253 : -0.4114585 
nnet RMSE 253 : 0.1432243 


s: 254 
logit 254 : -0.4471969 
logit mean 254 : -0.4389616 
logit RMSE 254 : 0.06991772 

boosting 254 : -0.4768784 
boosting mean 254 : -0.4889139 
boosting RMSE 254 : 0.1400050 

forest 254 : -0.397558 
forest mean 254 : -0.3825429 
forest RMSE 254 : 0.05618223 

nnet 254 : -0.675013 
nnet mean 254 : -0.4124961 
nnet RMSE 254 : 0.1439799 


s: 255 
logit 255 : -0.4463088 
logit mean 255 : -0.4389904 
logit RMSE 255 : 0.06984072 

boosting 255 : -0.6644075 
boosting mean 255 : -0.4896021 
boosting RMSE 255 : 0.1407078 

forest 255 : -0.4446273 
forest mean 255 : -0.3827864 
forest RMSE 255 : 0.05614156 

nnet 255 : -0.5560759 
nnet mean 255 : -0.4130592 
nnet RMSE 255 : 0.1440293 


s: 256 
logit 256 : -0.4500836 
logit mean 256 : -0.4390338 
logit RMSE 256 : 0.06977443 

boosting 256 : -0.5682283 
boosting mean 256 : -0.4899092 
boosting RMSE 256 : 0.1408258 

forest 256 : -0.3933595 
forest mean 256 : -0.3828277 
forest RMSE 256 : 0.05603334 

nnet 256 : -0.3033179 
nnet mean 256 : -0.4126305 
nnet RMSE 256 : 0.1438746 


s: 257 
logit 257 : -0.5150728 
logit mean 257 : -0.4393296 
logit RMSE 257 : 0.07000751 

boosting 257 : -0.7372279 
boosting mean 257 : -0.4908716 
boosting RMSE 257 : 0.1421169 

forest 257 : -0.4014751 
forest mean 257 : -0.3829002 
forest RMSE 257 : 0.0559243 

nnet 257 : -0.2482821 
nnet mean 257 : -0.411991 
nnet RMSE 257 : 0.143906 


s: 258 
logit 258 : -0.4321244 
logit mean 258 : -0.4393017 
logit RMSE 258 : 0.06990033 

boosting 258 : -0.649013 
boosting mean 258 : -0.4914845 
boosting RMSE 258 : 0.1426860 

forest 258 : -0.525986 
forest mean 258 : -0.3834548 
forest RMSE 258 : 0.05636422 

nnet 258 : -0.2893175 
nnet mean 258 : -0.4115155 
nnet RMSE 258 : 0.1437920 


s: 259 
logit 259 : -0.4775961 
logit mean 259 : -0.4394496 
logit RMSE 259 : 0.06993167 

boosting 259 : -0.4150217 
boosting mean 259 : -0.4911893 
boosting RMSE 259 : 0.1424133 

forest 259 : -0.3817865 
forest mean 259 : -0.3834484 
forest RMSE 259 : 0.05626669 

nnet 259 : -0.7217086 
nnet mean 259 : -0.4127132 
nnet RMSE 259 : 0.1448997 


s: 260 
logit 260 : -0.4154059 
logit mean 260 : -0.4393571 
logit RMSE 260 : 0.06980359 

boosting 260 : -0.3848531 
boosting mean 260 : -0.4907803 
boosting RMSE 260 : 0.1421423 

forest 260 : -0.4790398 
forest mean 260 : -0.3838160 
forest RMSE 260 : 0.05637191 

nnet 260 : -0.3042945 
nnet mean 260 : -0.4122962 
nnet RMSE 260 : 0.1447425 


s: 261 
logit 261 : -0.3579328 
logit mean 261 : -0.4390451 
logit RMSE 261 : 0.06971838 

boosting 261 : -0.5151274 
boosting mean 261 : -0.4908736 
boosting RMSE 261 : 0.1420486 

forest 261 : -0.3818277 
forest mean 261 : -0.3838084 
forest RMSE 261 : 0.05627505 

nnet 261 : -0.08839275 
nnet mean 261 : -0.4110552 
nnet RMSE 261 : 0.1457469 


s: 262 
logit 262 : -0.4727303 
logit mean 262 : -0.4391737 
logit RMSE 262 : 0.06973013 

boosting 262 : -0.4770629 
boosting mean 262 : -0.4908209 
boosting RMSE 262 : 0.1418571 

forest 262 : -0.3766937 
forest mean 262 : -0.3837813 
forest RMSE 262 : 0.05618601 

nnet 262 : -0.4211754 
nnet mean 262 : -0.4110938 
nnet RMSE 262 : 0.1454744 


s: 263 
logit 263 : -0.485716 
logit mean 263 : -0.4393507 
logit RMSE 263 : 0.06979784 

boosting 263 : -0.5365114 
boosting mean 263 : -0.4909946 
boosting RMSE 263 : 0.1418372 

forest 263 : -0.433352 
forest mean 263 : -0.3839698 
forest RMSE 263 : 0.05611679 

nnet 263 : -0.4321227 
nnet mean 263 : -0.4111738 
nnet RMSE 263 : 0.1452110 


s: 264 
logit 264 : -0.4850992 
logit mean 264 : -0.4395239 
logit RMSE 264 : 0.06986213 

boosting 264 : -0.4412979 
boosting mean 264 : -0.4908064 
boosting RMSE 264 : 0.1415911 

forest 264 : -0.3417395 
forest mean 264 : -0.3838098 
forest RMSE 264 : 0.05612506 

nnet 264 : -0.3396384 
nnet mean 264 : -0.4109028 
nnet RMSE 264 : 0.1449834 


s: 265 
logit 265 : -0.5098026 
logit mean 265 : -0.4397891 
logit RMSE 265 : 0.07005566 

boosting 265 : -0.5194655 
boosting mean 265 : -0.4909145 
boosting RMSE 265 : 0.1415141 

forest 265 : -0.383885 
forest mean 265 : -0.3838101 
forest RMSE 265 : 0.05602781 

nnet 265 : -0.5935348 
nnet mean 265 : -0.411592 
nnet RMSE 265 : 0.1451971 


s: 266 
logit 266 : -0.4793893 
logit mean 266 : -0.439938 
logit RMSE 266 : 0.07009308 

boosting 266 : -0.5621267 
boosting mean 266 : -0.4911822 
boosting RMSE 266 : 0.1415972 

forest 266 : -0.4327986 
forest mean 266 : -0.3839942 
forest RMSE 266 : 0.05595854 

nnet 266 : -0.4713982 
nnet mean 266 : -0.4118168 
nnet RMSE 266 : 0.14499 


s: 267 
logit 267 : -0.4528995 
logit mean 267 : -0.4399866 
logit RMSE 267 : 0.07003656 

boosting 267 : -0.5367294 
boosting mean 267 : -0.4913528 
boosting RMSE 267 : 0.1415793 

forest 267 : -0.4599581 
forest mean 267 : -0.3842787 
forest RMSE 267 : 0.05597406 

nnet 267 : -0.5770716 
nnet mean 267 : -0.4124358 
nnet RMSE 267 : 0.1451234 


s: 268 
logit 268 : -0.3965427 
logit mean 268 : -0.4398245 
logit RMSE 268 : 0.06990609 

boosting 268 : -0.4143420 
boosting mean 268 : -0.4910655 
boosting RMSE 268 : 0.1413176 

forest 268 : -0.3206927 
forest mean 268 : -0.3840415 
forest RMSE 268 : 0.05607917 

nnet 268 : -0.4927409 
nnet mean 268 : -0.4127354 
nnet RMSE 268 : 0.1449631 


s: 269 
logit 269 : -0.4812648 
logit mean 269 : -0.4399785 
logit RMSE 269 : 0.06995173 

boosting 269 : -0.6075224 
boosting mean 269 : -0.4914984 
boosting RMSE 269 : 0.1416211 

forest 269 : -0.4850502 
forest mean 269 : -0.384417 
forest RMSE 269 : 0.05621452 

nnet 269 : -0.5304081 
nnet mean 269 : -0.4131728 
nnet RMSE 269 : 0.1449117 


s: 270 
logit 270 : -0.4141949 
logit mean 270 : -0.439883 
logit RMSE 270 : 0.06982741 

boosting 270 : -0.6535114 
boosting mean 270 : -0.4920984 
boosting RMSE 270 : 0.1421980 

forest 270 : -0.3548216 
forest mean 270 : -0.3843074 
forest RMSE 270 : 0.05617765 

nnet 270 : -0.3367939 
nnet mean 270 : -0.41289 
nnet RMSE 270 : 0.1446943 


s: 271 
logit 271 : -0.4290305 
logit mean 271 : -0.439843 
logit RMSE 271 : 0.06972077 

boosting 271 : -0.6575941 
boosting mean 271 : -0.4927091 
boosting RMSE 271 : 0.1427954 

forest 271 : -0.411665 
forest mean 271 : -0.3844083 
forest RMSE 271 : 0.05607838 

nnet 271 : -0.5266327 
nnet mean 271 : -0.4133097 
nnet RMSE 271 : 0.1446318 


s: 272 
logit 272 : -0.5285436 
logit mean 272 : -0.4401691 
logit RMSE 272 : 0.07002758 

boosting 272 : -0.5338237 
boosting mean 272 : -0.4928603 
boosting RMSE 272 : 0.1427634 

forest 272 : -0.3705271 
forest mean 272 : -0.3843573 
forest RMSE 272 : 0.05600372 

nnet 272 : -0.4608122 
nnet mean 272 : -0.4134843 
nnet RMSE 272 : 0.1444127 


s: 273 
logit 273 : -0.4395045 
logit mean 273 : -0.4401666 
logit RMSE 273 : 0.06994009 

boosting 273 : -0.6627167 
boosting mean 273 : -0.4934825 
boosting RMSE 273 : 0.1433860 

forest 273 : -0.3641729 
forest mean 273 : -0.3842834 
forest RMSE 273 : 0.05594309 

nnet 273 : -0.2450979 
nnet mean 273 : -0.4128675 
nnet RMSE 273 : 0.1444525 


s: 274 
logit 274 : -0.3692684 
logit mean 274 : -0.4399079 
logit RMSE 274 : 0.06983703 

boosting 274 : -0.05802002 
boosting mean 274 : -0.4918932 
boosting RMSE 274 : 0.1446076 

forest 274 : -0.3126331 
forest mean 274 : -0.3840219 
forest RMSE 274 : 0.0560898 

nnet 274 : -0.3460039 
nnet mean 274 : -0.4126235 
nnet RMSE 274 : 0.1442256 


s: 275 
logit 275 : -0.463008 
logit mean 275 : -0.4399919 
logit RMSE 275 : 0.0698134 

boosting 275 : -0.5020871 
boosting mean 275 : -0.4919302 
boosting RMSE 275 : 0.1444756 

forest 275 : -0.2950698 
forest mean 275 : -0.3836984 
forest RMSE 275 : 0.05634415 

nnet 275 : -0.6637487 
nnet mean 275 : -0.4135367 
nnet RMSE 275 : 0.144839 


s: 276 
logit 276 : -0.4538762 
logit mean 276 : -0.4400422 
logit RMSE 276 : 0.06976223 

boosting 276 : -0.4172137 
boosting mean 276 : -0.4916595 
boosting RMSE 276 : 0.1442174 

forest 276 : -0.3364945 
forest mean 276 : -0.3835274 
forest RMSE 276 : 0.05637173 

nnet 276 : -0.5811234 
nnet mean 276 : -0.4141439 
nnet RMSE 276 : 0.1449869 


s: 277 
logit 277 : -0.4009483 
logit mean 277 : -0.4399011 
logit RMSE 277 : 0.06963622 

boosting 277 : -0.5508026 
boosting mean 277 : -0.491873 
boosting RMSE 277 : 0.1442417 

forest 277 : -0.3706798 
forest mean 277 : -0.383481 
forest RMSE 277 : 0.05629746 

nnet 277 : -0.4237421 
nnet mean 277 : -0.4141785 
nnet RMSE 277 : 0.1447319 


s: 278 
logit 278 : -0.5094318 
logit mean 278 : -0.4401512 
logit RMSE 278 : 0.06982003 

boosting 278 : -0.8111424 
boosting mean 278 : -0.4930215 
boosting RMSE 278 : 0.1460783 

forest 278 : -0.3963975 
forest mean 278 : -0.3835274 
forest RMSE 278 : 0.05619653 

nnet 278 : -0.5012208 
nnet mean 278 : -0.4144916 
nnet RMSE 278 : 0.1445989 


s: 279 
logit 279 : -0.5235613 
logit mean 279 : -0.4404501 
logit RMSE 279 : 0.07008627 

boosting 279 : -0.6163207 
boosting mean 279 : -0.4934634 
boosting RMSE 279 : 0.1463903 

forest 279 : -0.4378049 
forest mean 279 : -0.383722 
forest RMSE 279 : 0.05614137 

nnet 279 : -0.502126 
nnet mean 279 : -0.4148057 
nnet RMSE 279 : 0.1444690 


s: 280 
logit 280 : -0.5212647 
logit mean 280 : -0.4407388 
logit RMSE 280 : 0.07033534 

boosting 280 : -0.3364392 
boosting mean 280 : -0.4929026 
boosting RMSE 280 : 0.146178 

forest 280 : -0.4366734 
forest mean 280 : -0.3839111 
forest RMSE 280 : 0.05608387 

nnet 280 : -0.3282691 
nnet mean 280 : -0.4144967 
nnet RMSE 280 : 0.1442745 


s: 281 
logit 281 : -0.3855567 
logit mean 281 : -0.4405424 
logit RMSE 281 : 0.07021537 

boosting 281 : -0.5564529 
boosting mean 281 : -0.4931288 
boosting RMSE 281 : 0.1462158 

forest 281 : -0.3949530 
forest mean 281 : -0.3839504 
forest RMSE 281 : 0.05598479 

nnet 281 : -0.6418029 
nnet mean 281 : -0.4153056 
nnet RMSE 281 : 0.1447381 


s: 282 
logit 282 : -0.412283 
logit mean 282 : -0.4404422 
logit RMSE 282 : 0.07009458 

boosting 282 : -0.4406124 
boosting mean 282 : -0.4929426 
boosting RMSE 282 : 0.1459764 

forest 282 : -0.4266935 
forest mean 282 : -0.384102 
forest RMSE 282 : 0.05590804 

nnet 282 : -0.3357795 
nnet mean 282 : -0.4150236 
nnet RMSE 282 : 0.1445318 


s: 283 
logit 283 : -0.4991927 
logit mean 283 : -0.4406498 
logit RMSE 283 : 0.07021863 

boosting 283 : -0.3827005 
boosting mean 283 : -0.492553 
boosting RMSE 283 : 0.1457219 

forest 283 : -0.4363129 
forest mean 283 : -0.3842865 
forest RMSE 283 : 0.05585091 

nnet 283 : -0.3926921 
nnet mean 283 : -0.4149447 
nnet RMSE 283 : 0.1442769 


s: 284 
logit 284 : -0.4739441 
logit mean 284 : -0.440767 
logit RMSE 284 : 0.0702321 

boosting 284 : -0.6090844 
boosting mean 284 : -0.4929633 
boosting RMSE 284 : 0.1459932 

forest 284 : -0.3847706 
forest mean 284 : -0.3842882 
forest RMSE 284 : 0.05575981 

nnet 284 : -0.5645671 
nnet mean 284 : -0.4154715 
nnet RMSE 284 : 0.1443534 


s: 285 
logit 285 : -0.4601018 
logit mean 285 : -0.4408348 
logit RMSE 285 : 0.0701991 

boosting 285 : -0.5275673 
boosting mean 285 : -0.4930848 
boosting RMSE 285 : 0.1459327 

forest 285 : -0.4579423 
forest mean 285 : -0.3845466 
forest RMSE 285 : 0.05576762 

nnet 285 : -0.468019 
nnet mean 285 : -0.4156559 
nnet RMSE 285 : 0.1441562 


s: 286 
logit 286 : -0.3920333 
logit mean 286 : -0.4406642 
logit RMSE 286 : 0.07007786 

boosting 286 : -0.5138613 
boosting mean 286 : -0.4931574 
boosting RMSE 286 : 0.1458328 

forest 286 : -0.3270312 
forest mean 286 : -0.3843455 
forest RMSE 286 : 0.055837 

nnet 286 : -0.3896084 
nnet mean 286 : -0.4155648 
nnet RMSE 286 : 0.1439053 


s: 287 
logit 287 : -0.4789868 
logit mean 287 : -0.4407977 
logit RMSE 287 : 0.07011086 

boosting 287 : -0.4160761 
boosting mean 287 : -0.4928888 
boosting RMSE 287 : 0.1455816 

forest 287 : -0.4216087 
forest mean 287 : -0.3844753 
forest RMSE 287 : 0.05575423 

nnet 287 : -0.3013084 
nnet mean 287 : -0.4151667 
nnet RMSE 287 : 0.1437724 


s: 288 
logit 288 : -0.4685783 
logit mean 288 : -0.4408942 
logit RMSE 288 : 0.0701056 

boosting 288 : -0.4841976 
boosting mean 288 : -0.4928586 
boosting RMSE 288 : 0.1454133 

forest 288 : -0.4090467 
forest mean 288 : -0.3845607 
forest RMSE 288 : 0.0556599 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 288 : -0.2247345 
nnet mean 288 : -0.4145055 
nnet RMSE 288 : 0.1438937 


s: 289 
logit 289 : -0.3751016 
logit mean 289 : -0.4406665 
logit RMSE 289 : 0.06999953 

boosting 289 : -0.4968435 
boosting mean 289 : -0.4928724 
boosting RMSE 289 : 0.1452733 

forest 289 : -0.3728982 
forest mean 289 : -0.3845203 
forest RMSE 289 : 0.05558639 

nnet 289 : -0.4815574 
nnet mean 289 : -0.4147375 
nnet RMSE 289 : 0.1437246 


s: 290 
logit 290 : -0.3659172 
logit mean 290 : -0.4404088 
logit RMSE 290 : 0.06990739 

boosting 290 : -0.4063457 
boosting mean 290 : -0.4925741 
boosting RMSE 290 : 0.1450230 

forest 290 : -0.3986982 
forest mean 290 : -0.3845692 
forest RMSE 290 : 0.05549052 

nnet 290 : -0.2142445 
nnet mean 290 : -0.4140461 
nnet RMSE 290 : 0.1438907 


s: 291 
logit 291 : -0.4177845 
logit mean 291 : -0.440331 
logit RMSE 291 : 0.06979496 

boosting 291 : -0.3124653 
boosting mean 291 : -0.4919551 
boosting RMSE 291 : 0.1448646 

forest 291 : -0.3603067 
forest mean 291 : -0.3844858 
forest RMSE 291 : 0.05544394 

nnet 291 : -0.6339545 
nnet mean 291 : -0.4148018 
nnet RMSE 291 : 0.1442964 


s: 292 
logit 292 : -0.4355883 
logit mean 292 : -0.4403148 
logit RMSE 292 : 0.06970646 

boosting 292 : -0.4271198 
boosting mean 292 : -0.4917331 
boosting RMSE 292 : 0.144625 

forest 292 : -0.3797242 
forest mean 292 : -0.3844695 
forest RMSE 292 : 0.05536164 

nnet 292 : -0.3045956 
nnet mean 292 : -0.4144244 
nnet RMSE 292 : 0.1441573 


s: 293 
logit 293 : -0.4348789 
logit mean 293 : -0.4402962 
logit RMSE 293 : 0.06961723 

boosting 293 : -0.468299 
boosting mean 293 : -0.4916531 
boosting RMSE 293 : 0.1444331 

forest 293 : -0.3790515 
forest mean 293 : -0.384451 
forest RMSE 293 : 0.05528063 

nnet 293 : -0.3526143 
nnet mean 293 : -0.4142135 
nnet RMSE 293 : 0.1439377 


s: 294 
logit 294 : -0.3467983 
logit mean 294 : -0.4399782 
logit RMSE 294 : 0.06956796 

boosting 294 : -0.4104457 
boosting mean 294 : -0.4913769 
boosting RMSE 294 : 0.1441886 

forest 294 : -0.3027741 
forest mean 294 : -0.3841732 
forest RMSE 294 : 0.05547708 

nnet 294 : -0.08272906 
nnet mean 294 : -0.413086 
nnet RMSE 294 : 0.1448792 


s: 295 
logit 295 : -0.4083576 
logit mean 295 : -0.439871 
logit RMSE 295 : 0.06945166 

boosting 295 : -0.6245754 
boosting mean 295 : -0.4918284 
boosting RMSE 295 : 0.1445366 

forest 295 : -0.4347584 
forest mean 295 : -0.3843447 
forest RMSE 295 : 0.05541993 

nnet 295 : -0.5172076 
nnet mean 295 : -0.4134389 
nnet RMSE 295 : 0.1447943 


s: 296 
logit 296 : -0.4952779 
logit mean 296 : -0.4400582 
logit RMSE 296 : 0.06955505 

boosting 296 : -0.4997088 
boosting mean 296 : -0.491855 
boosting RMSE 296 : 0.1444086 

forest 296 : -0.3671013 
forest mean 296 : -0.3842864 
forest RMSE 296 : 0.05535927 

nnet 296 : -0.6112884 
nnet mean 296 : -0.4141073 
nnet RMSE 296 : 0.1450703 


s: 297 
logit 297 : -0.531727 
logit mean 297 : -0.4403669 
logit RMSE 297 : 0.06985729 

boosting 297 : -0.6156475 
boosting mean 297 : -0.4922719 
boosting RMSE 297 : 0.1447073 

forest 297 : -0.3454368 
forest mean 297 : -0.3841556 
forest RMSE 297 : 0.05535661 

nnet 297 : -0.5185973 
nnet mean 297 : -0.4144592 
nnet RMSE 297 : 0.1449893 


s: 298 
logit 298 : -0.5245537 
logit mean 298 : -0.4406494 
logit RMSE 298 : 0.07011222 

boosting 298 : -0.6963832 
boosting mean 298 : -0.4929568 
boosting RMSE 298 : 0.1454809 

forest 298 : -0.3390822 
forest mean 298 : -0.3840044 
forest RMSE 298 : 0.05537621 

nnet 298 : -0.5781455 
nnet mean 298 : -0.4150084 
nnet RMSE 298 : 0.1451132 


s: 299 
logit 299 : -0.4669309 
logit mean 299 : -0.4407373 
logit RMSE 299 : 0.07010182 

boosting 299 : -0.2369987 
boosting mean 299 : -0.4921007 
boosting RMSE 299 : 0.1455431 

forest 299 : -0.4037724 
forest mean 299 : -0.3840705 
forest RMSE 299 : 0.05528396 

nnet 299 : -0.2952805 
nnet mean 299 : -0.414608 
nnet RMSE 299 : 0.1449968 


s: 300 
logit 300 : -0.5101948 
logit mean 300 : -0.4409688 
logit RMSE 300 : 0.07027347 

boosting 300 : -0.433351 
boosting mean 300 : -0.4919049 
boosting RMSE 300 : 0.1453130 

forest 300 : -0.3706155 
forest mean 300 : -0.3840256 
forest RMSE 300 : 0.05521781 

nnet 300 : -0.4136936 
nnet mean 300 : -0.4146050 
nnet RMSE 300 : 0.1447571 


s: 301 
logit 301 : -0.4496408 
logit mean 301 : -0.4409976 
logit RMSE 301 : 0.07021496 

boosting 301 : -0.4764283 
boosting mean 301 : -0.4918535 
boosting RMSE 301 : 0.1451383 

forest 301 : -0.4765069 
forest mean 301 : -0.3843329 
forest RMSE 301 : 0.05530211 

nnet 301 : -0.3944625 
nnet mean 301 : -0.414538 
nnet RMSE 301 : 0.1445168 


s: 302 
logit 302 : -0.4683535 
logit mean 302 : -0.4410882 
logit RMSE 302 : 0.07020888 

boosting 302 : -0.3455882 
boosting mean 302 : -0.4913692 
boosting RMSE 302 : 0.1449317 

forest 302 : -0.360436 
forest mean 302 : -0.3842537 
forest RMSE 302 : 0.05525739 

nnet 302 : -0.4176147 
nnet mean 302 : -0.4145482 
nnet RMSE 302 : 0.1442809 


s: 303 
logit 303 : -0.455485 
logit mean 303 : -0.4411357 
logit RMSE 303 : 0.07016537 

boosting 303 : -0.5652843 
boosting mean 303 : -0.4916131 
boosting RMSE 303 : 0.1450035 

forest 303 : -0.4860517 
forest mean 303 : -0.3845897 
forest RMSE 303 : 0.05538719 

nnet 303 : -0.4078960 
nnet mean 303 : -0.4145263 
nnet RMSE 303 : 0.1440434 


s: 304 
logit 304 : -0.4732408 
logit mean 304 : -0.4412413 
logit RMSE 304 : 0.07017571 

boosting 304 : -0.4726386 
boosting mean 304 : -0.4915507 
boosting RMSE 304 : 0.1448248 

forest 304 : -0.4633602 
forest mean 304 : -0.3848488 
forest RMSE 304 : 0.0554153 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 304 : -0.2644422 
nnet mean 304 : -0.4140326 
nnet RMSE 304 : 0.1440163 


s: 305 
logit 305 : -0.4746414 
logit mean 305 : -0.4413508 
logit RMSE 305 : 0.07019081 

boosting 305 : -0.3816835 
boosting mean 305 : -0.4911905 
boosting RMSE 305 : 0.1445910 

forest 305 : -0.3194007 
forest mean 305 : -0.3846342 
forest RMSE 305 : 0.05551654 

nnet 305 : -0.3650932 
nnet mean 305 : -0.4138721 
nnet RMSE 305 : 0.1437939 


s: 306 
logit 306 : -0.4220072 
logit mean 306 : -0.4412876 
logit RMSE 306 : 0.07008732 

boosting 306 : -0.5514988 
boosting mean 306 : -0.4913876 
boosting RMSE 306 : 0.1446141 

forest 306 : -0.3688188 
forest mean 306 : -0.3845826 
forest RMSE 306 : 0.05545441 

nnet 306 : -0.4270897 
nnet mean 306 : -0.4139153 
nnet RMSE 306 : 0.1435671 


s: 307 
logit 307 : -0.4834011 
logit mean 307 : -0.4414248 
logit RMSE 307 : 0.07013479 

boosting 307 : -0.5231899 
boosting mean 307 : -0.4914912 
boosting RMSE 307 : 0.1445494 

forest 307 : -0.2829881 
forest mean 307 : -0.3842516 
forest RMSE 307 : 0.05576534 

nnet 307 : -0.5502123 
nnet mean 307 : -0.4143593 
nnet RMSE 307 : 0.1435892 


s: 308 
logit 308 : -0.4446293 
logit mean 308 : -0.4414352 
logit RMSE 308 : 0.070067 

boosting 308 : -0.5841514 
boosting mean 308 : -0.491792 
boosting RMSE 308 : 0.1446956 

forest 308 : -0.4356748 
forest mean 308 : -0.3844186 
forest RMSE 308 : 0.05571183 

nnet 308 : -0.3756255 
nnet mean 308 : -0.4142335 
nnet RMSE 308 : 0.1433627 


s: 309 
logit 309 : -0.4600996 
logit mean 309 : -0.4414956 
logit RMSE 309 : 0.07003704 

boosting 309 : -0.4710322 
boosting mean 309 : -0.4917248 
boosting RMSE 309 : 0.1445177 

forest 309 : -0.3387282 
forest mean 309 : -0.3842707 
forest RMSE 309 : 0.05573072 

nnet 309 : -0.5396252 
nnet mean 309 : -0.4146393 
nnet RMSE 309 : 0.1433507 


s: 310 
logit 310 : -0.3258859 
logit mean 310 : -0.4411227 
logit RMSE 310 : 0.07005057 

boosting 310 : -0.614585 
boosting mean 310 : -0.4921211 
boosting RMSE 310 : 0.1447983 

forest 310 : -0.3530541 
forest mean 310 : -0.38417 
forest RMSE 310 : 0.05570461 

nnet 310 : -0.5325578 
nnet mean 310 : -0.4150197 
nnet RMSE 310 : 0.1433172 


s: 311 
logit 311 : -0.3819489 
logit mean 311 : -0.4409324 
logit RMSE 311 : 0.06994535 

boosting 311 : -0.5161283 
boosting mean 311 : -0.4921983 
boosting RMSE 311 : 0.1447152 

forest 311 : -0.3716741 
forest mean 311 : -0.3841298 
forest RMSE 311 : 0.05563817 

nnet 311 : -0.3460029 
nnet mean 311 : -0.4147978 
nnet RMSE 311 : 0.1431194 


s: 312 
logit 312 : -0.4533309 
logit mean 312 : -0.4409721 
logit RMSE 312 : 0.0698984 

boosting 312 : -0.6866866 
boosting mean 312 : -0.4928217 
boosting RMSE 312 : 0.1453919 

forest 312 : -0.4090665 
forest mean 312 : -0.3842098 
forest RMSE 312 : 0.05555131 

nnet 312 : -0.3969143 
nnet mean 312 : -0.4147405 
nnet RMSE 312 : 0.1428899 


s: 313 
logit 313 : -0.3721029 
logit mean 313 : -0.4407521 
logit RMSE 313 : 0.06980447 

boosting 313 : -0.3168871 
boosting mean 313 : -0.4922596 
boosting RMSE 313 : 0.1452354 

forest 313 : -0.4106374 
forest mean 313 : -0.3842942 
forest RMSE 313 : 0.05546576 

nnet 313 : -0.2512188 
nnet mean 313 : -0.414218 
nnet RMSE 313 : 0.1429091 


s: 314 
logit 314 : -0.4328977 
logit mean 314 : -0.4407271 
logit RMSE 314 : 0.06971795 

boosting 314 : -0.4492574 
boosting mean 314 : -0.4921227 
boosting RMSE 314 : 0.1450306 

forest 314 : -0.326722 
forest mean 314 : -0.3841108 
forest RMSE 314 : 0.05553155 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 314 : -0.1969105 
nnet mean 314 : -0.413526 
nnet RMSE 314 : 0.1431410 


s: 315 
logit 315 : -0.435673 
logit mean 315 : -0.440711 
logit RMSE 315 : 0.06963621 

boosting 315 : -0.6500007 
boosting mean 315 : -0.4926239 
boosting RMSE 315 : 0.1454837 

forest 315 : -0.4581143 
forest mean 315 : -0.3843458 
forest RMSE 315 : 0.05553994 

nnet 315 : -0.4403879 
nnet mean 315 : -0.4136112 
nnet RMSE 315 : 0.1429317 


s: 316 
logit 316 : -0.3986874 
logit mean 316 : -0.4405781 
logit RMSE 316 : 0.06952598 

boosting 316 : -0.3754042 
boosting mean 316 : -0.4922529 
boosting RMSE 316 : 0.1452599 

forest 316 : -0.3864603 
forest mean 316 : -0.3843525 
forest RMSE 316 : 0.05545722 

nnet 316 : -0.3141881 
nnet mean 316 : -0.4132966 
nnet RMSE 316 : 0.1427870 


s: 317 
logit 317 : -0.3684451 
logit mean 317 : -0.4403505 
logit RMSE 317 : 0.06943885 

boosting 317 : -0.5504962 
boosting mean 317 : -0.4924366 
boosting RMSE 317 : 0.1452768 

forest 317 : -0.3923031 
forest mean 317 : -0.3843776 
forest RMSE 317 : 0.05537137 

nnet 317 : -0.5100608 
nnet mean 317 : -0.4136019 
nnet RMSE 317 : 0.1426955 


s: 318 
logit 318 : -0.3715402 
logit mean 318 : -0.4401341 
logit RMSE 318 : 0.06934795 

boosting 318 : -0.7093681 
boosting mean 318 : -0.4931188 
boosting RMSE 318 : 0.1460820 

forest 318 : -0.3918748 
forest mean 318 : -0.3844011 
forest RMSE 318 : 0.05528612 

nnet 318 : -0.2125374 
nnet mean 318 : -0.4129696 
nnet RMSE 318 : 0.1428583 


s: 319 
logit 319 : -0.4540186 
logit mean 319 : -0.4401776 
logit RMSE 319 : 0.0693052 

boosting 319 : -0.5753947 
boosting mean 319 : -0.4933767 
boosting RMSE 319 : 0.1461830 

forest 319 : -0.4599838 
forest mean 319 : -0.3846381 
forest RMSE 319 : 0.05530147 

nnet 319 : -0.4993869 
nnet mean 319 : -0.4132405 
nnet RMSE 319 : 0.1427427 


s: 320 
logit 320 : -0.5340776 
logit mean 320 : -0.4404711 
logit RMSE 320 : 0.06960156 

boosting 320 : -0.5753889 
boosting mean 320 : -0.493633 
boosting RMSE 320 : 0.1462834 

forest 320 : -0.4052878 
forest mean 320 : -0.3847026 
forest RMSE 320 : 0.05521578 

nnet 320 : -0.4424255 
nnet mean 320 : -0.4133317 
nnet RMSE 320 : 0.1425392 


s: 321 
logit 321 : -0.4725146 
logit mean 321 : -0.4405709 
logit RMSE 321 : 0.06961083 

boosting 321 : -0.4353099 
boosting mean 321 : -0.4934513 
boosting RMSE 321 : 0.1460686 

forest 321 : -0.3755682 
forest mean 321 : -0.3846741 
forest RMSE 321 : 0.05514657 

nnet 321 : -0.4109636 
nnet mean 321 : -0.4133243 
nnet RMSE 321 : 0.1423184 


s: 322 
logit 322 : -0.497312 
logit mean 322 : -0.4407471 
logit RMSE 322 : 0.0697139 

boosting 322 : -0.4701286 
boosting mean 322 : -0.4933789 
boosting RMSE 322 : 0.145894 

forest 322 : -0.3864286 
forest mean 322 : -0.3846796 
forest RMSE 322 : 0.05506607 

nnet 322 : -0.4039352 
nnet mean 322 : -0.4132952 
nnet RMSE 322 : 0.1420974 


s: 323 
logit 323 : -0.4257542 
logit mean 323 : -0.4407007 
logit RMSE 323 : 0.06962065 

boosting 323 : -0.5619151 
boosting mean 323 : -0.4935911 
boosting RMSE 323 : 0.1459463 

forest 323 : -0.3663905 
forest mean 323 : -0.384623 
forest RMSE 323 : 0.05501255 

nnet 323 : -0.4472347 
nnet mean 323 : -0.4134002 
nnet RMSE 323 : 0.1419016 


s: 324 
logit 324 : -0.476181 
logit mean 324 : -0.4408102 
logit RMSE 324 : 0.06964184 

boosting 324 : -0.4577895 
boosting mean 324 : -0.4934806 
boosting RMSE 324 : 0.1457563 

forest 324 : -0.4048899 
forest mean 324 : -0.3846855 
forest RMSE 324 : 0.05492826 

nnet 324 : -0.3803628 
nnet mean 324 : -0.4132983 
nnet RMSE 324 : 0.1416866 


s: 325 
logit 325 : -0.4997838 
logit mean 325 : -0.4409917 
logit RMSE 325 : 0.06975457 

boosting 325 : -0.5259736 
boosting mean 325 : -0.4935806 
boosting RMSE 325 : 0.1456995 

forest 325 : -0.4247592 
forest mean 325 : -0.3848088 
forest RMSE 325 : 0.05486089 

nnet 325 : -0.4119428 
nnet mean 325 : -0.4132941 
nnet RMSE 325 : 0.1414700 


s: 326 
logit 326 : -0.4451876 
logit mean 326 : -0.4410045 
logit RMSE 326 : 0.06969245 

boosting 326 : -0.5507224 
boosting mean 326 : -0.4937558 
boosting RMSE 326 : 0.1457152 

forest 326 : -0.3818136 
forest mean 326 : -0.3847996 
forest RMSE 326 : 0.05478594 

nnet 326 : -0.3448292 
nnet mean 326 : -0.4130841 
nnet RMSE 326 : 0.1412859 


s: 327 
logit 327 : -0.5000884 
logit mean 327 : -0.4411852 
logit RMSE 327 : 0.06980559 

boosting 327 : -0.3948866 
boosting mean 327 : -0.4934535 
boosting RMSE 327 : 0.1454925 

forest 327 : -0.3895284 
forest mean 327 : -0.3848141 
forest RMSE 327 : 0.05470517 

nnet 327 : -0.6330165 
nnet mean 327 : -0.4137566 
nnet RMSE 327 : 0.1416570 


s: 328 
logit 328 : -0.4526895 
logit mean 328 : -0.4412203 
logit RMSE 328 : 0.06975978 

boosting 328 : -0.6227533 
boosting mean 328 : -0.4938477 
boosting RMSE 328 : 0.1457903 

forest 328 : -0.4102727 
forest mean 328 : -0.3848917 
forest RMSE 328 : 0.05462466 

nnet 328 : -0.3945416 
nnet mean 328 : -0.4136981 
nnet RMSE 328 : 0.1414412 


s: 329 
logit 329 : -0.3676847 
logit mean 329 : -0.4409968 
logit RMSE 329 : 0.06967647 

boosting 329 : -0.3937792 
boosting mean 329 : -0.4935435 
boosting RMSE 329 : 0.1455690 

forest 329 : -0.3684393 
forest mean 329 : -0.3848417 
forest RMSE 329 : 0.05456933 

nnet 329 : -0.3923390 
nnet mean 329 : -0.4136331 
nnet RMSE 329 : 0.1412268 


s: 330 
logit 330 : -0.4757986 
logit mean 330 : -0.4411022 
logit RMSE 330 : 0.06969583 

boosting 330 : -0.4752861 
boosting mean 330 : -0.4934882 
boosting RMSE 330 : 0.1454073 

forest 330 : -0.4244984 
forest mean 330 : -0.3849619 
forest RMSE 330 : 0.05450327 

nnet 330 : -0.7524292 
nnet mean 330 : -0.4146598 
nnet RMSE 330 : 0.1423409 


s: 331 
logit 331 : -0.460996 
logit mean 331 : -0.4411624 
logit RMSE 331 : 0.06967118 

boosting 331 : -0.7073856 
boosting mean 331 : -0.4941344 
boosting RMSE 331 : 0.1461673 

forest 331 : -0.3389263 
forest mean 331 : -0.3848228 
forest RMSE 331 : 0.05452431 

nnet 331 : -0.3855733 
nnet mean 331 : -0.4145719 
nnet RMSE 331 : 0.1421280 


s: 332 
logit 332 : -0.3847552 
logit mean 332 : -0.4409924 
logit RMSE 332 : 0.06957121 

boosting 332 : -0.4255568 
boosting mean 332 : -0.4939279 
boosting RMSE 332 : 0.1459537 

forest 332 : -0.355502 
forest mean 332 : -0.3847345 
forest RMSE 332 : 0.05449688 

nnet 332 : -0.8426386 
nnet mean 332 : -0.4158613 
nnet RMSE 332 : 0.143978 


s: 333 
logit 333 : -0.5529484 
logit mean 333 : -0.4413287 
logit RMSE 333 : 0.06997048 

boosting 333 : -0.7713189 
boosting mean 333 : -0.4947609 
boosting RMSE 333 : 0.1471481 

forest 333 : -0.5242634 
forest mean 333 : -0.3851535 
forest RMSE 333 : 0.05483942 

nnet 333 : -0.291738 
nnet mean 333 : -0.4154885 
nnet RMSE 333 : 0.143884 


s: 334 
logit 334 : -0.3928812 
logit mean 334 : -0.4411836 
logit RMSE 334 : 0.06986674 

boosting 334 : -0.5216628 
boosting mean 334 : -0.4948414 
boosting RMSE 334 : 0.1470784 

forest 334 : -0.3866524 
forest mean 334 : -0.385158 
forest RMSE 334 : 0.05476214 

nnet 334 : -0.5286567 
nnet mean 334 : -0.4158274 
nnet RMSE 334 : 0.1438408 


s: 335 
logit 335 : -0.4480327 
logit mean 335 : -0.4412040 
logit RMSE 335 : 0.06981173 

boosting 335 : -0.6488308 
boosting mean 335 : -0.4953011 
boosting RMSE 335 : 0.1474866 

forest 335 : -0.4120671 
forest mean 335 : -0.3852383 
forest RMSE 335 : 0.05468432 

nnet 335 : -0.5889882 
nnet mean 335 : -0.4163443 
nnet RMSE 335 : 0.1439967 


s: 336 
logit 336 : -0.541353 
logit mean 336 : -0.4415021 
logit RMSE 336 : 0.070133 

boosting 336 : -0.6871255 
boosting mean 336 : -0.495872 
boosting RMSE 336 : 0.1480977 

forest 336 : -0.3823698 
forest mean 336 : -0.3852298 
forest RMSE 336 : 0.05461135 

nnet 336 : -0.4420903 
nnet mean 336 : -0.4164209 
nnet RMSE 336 : 0.1438005 


s: 337 
logit 337 : -0.5306469 
logit mean 337 : -0.4417666 
logit RMSE 337 : 0.07038957 

boosting 337 : -0.6018912 
boosting mean 337 : -0.4961866 
boosting RMSE 337 : 0.1482862 

forest 337 : -0.3828303 
forest mean 337 : -0.3852226 
forest RMSE 337 : 0.05453828 

nnet 337 : -0.5329628 
nnet mean 337 : -0.4167667 
nnet RMSE 337 : 0.1437696 


s: 338 
logit 338 : -0.3789047 
logit mean 338 : -0.4415807 
logit RMSE 338 : 0.07029473 

boosting 338 : -0.5117887 
boosting mean 338 : -0.4962328 
boosting RMSE 338 : 0.1481914 

forest 338 : -0.3349821 
forest mean 338 : -0.385074 
forest RMSE 338 : 0.05457226 

nnet 338 : -0.3513212 
nnet mean 338 : -0.4165731 
nnet RMSE 338 : 0.1435812 


s: 339 
logit 339 : -0.4258586 
logit mean 339 : -0.4415343 
logit RMSE 339 : 0.07020503 

boosting 339 : -0.41472 
boosting mean 339 : -0.4959923 
boosting RMSE 339 : 0.1479749 

forest 339 : -0.432587 
forest mean 339 : -0.3852142 
forest RMSE 339 : 0.05452044 

nnet 339 : -0.3953319 
nnet mean 339 : -0.4165104 
nnet RMSE 339 : 0.1433695 


s: 340 
logit 340 : -0.5619929 
logit mean 340 : -0.4418886 
logit RMSE 340 : 0.07065006 

boosting 340 : -0.3403858 
boosting mean 340 : -0.4955346 
boosting RMSE 340 : 0.1477925 

forest 340 : -0.3408020 
forest mean 340 : -0.3850835 
forest RMSE 340 : 0.05453479 

nnet 340 : -0.3805242 
nnet mean 340 : -0.4164046 
nnet RMSE 340 : 0.1431624 


s: 341 
logit 341 : -0.3582607 
logit mean 341 : -0.4416433 
logit RMSE 341 : 0.07058259 

boosting 341 : -0.4483572 
boosting mean 341 : -0.4953963 
boosting RMSE 341 : 0.1475988 

forest 341 : -0.4714529 
forest mean 341 : -0.3853368 
forest RMSE 341 : 0.05459207 

nnet 341 : -0.2739872 
nnet mean 341 : -0.4159869 
nnet RMSE 341 : 0.1431151 


s: 342 
logit 342 : -0.4195856 
logit mean 342 : -0.4415788 
logit RMSE 342 : 0.07048728 

boosting 342 : -0.5424037 
boosting mean 342 : -0.4955337 
boosting RMSE 342 : 0.1475839 

forest 342 : -0.4525914 
forest mean 342 : -0.3855335 
forest RMSE 342 : 0.05458632 

nnet 342 : -0.3190068 
nnet mean 342 : -0.4157034 
nnet RMSE 342 : 0.1429728 


s: 343 
logit 343 : -0.4843654 
logit mean 343 : -0.4417036 
logit RMSE 343 : 0.07053171 

boosting 343 : -0.3119211 
boosting mean 343 : -0.4949984 
boosting RMSE 343 : 0.1474453 

forest 343 : -0.2905296 
forest mean 343 : -0.3852565 
forest RMSE 343 : 0.05482625 

nnet 343 : -0.3090154 
nnet mean 343 : -0.4153923 
nnet RMSE 343 : 0.1428487 


s: 344 
logit 344 : -0.445837 
logit mean 344 : -0.4417156 
logit RMSE 344 : 0.07047247 

boosting 344 : -0.804872 
boosting mean 344 : -0.4958992 
boosting RMSE 344 : 0.1488403 

forest 344 : -0.3744912 
forest mean 344 : -0.3852252 
forest RMSE 344 : 0.05476378 

nnet 344 : -0.3557659 
nnet mean 344 : -0.415219 
nnet RMSE 344 : 0.1426609 


s: 345 
logit 345 : -0.3143667 
logit mean 345 : -0.4413465 
logit RMSE 345 : 0.07052112 

boosting 345 : -0.5363091 
boosting mean 345 : -0.4960163 
boosting RMSE 345 : 0.1488055 

forest 345 : -0.3324177 
forest mean 345 : -0.3850721 
forest RMSE 345 : 0.05480527 

nnet 345 : -0.4742865 
nnet mean 345 : -0.4153902 
nnet RMSE 345 : 0.1425101 


s: 346 
logit 346 : -0.5650391 
logit mean 346 : -0.4417039 
logit RMSE 346 : 0.0709759 

boosting 346 : -0.3288897 
boosting mean 346 : -0.4955333 
boosting RMSE 346 : 0.1486395 

forest 346 : -0.3063506 
forest mean 346 : -0.3848446 
forest RMSE 346 : 0.05495711 

nnet 346 : -0.3970806 
nnet mean 346 : -0.4153373 
nnet RMSE 346 : 0.1423041 


s: 347 
logit 347 : -0.4638115 
logit mean 347 : -0.4417677 
logit RMSE 347 : 0.07095629 

boosting 347 : -0.5229602 
boosting mean 347 : -0.4956124 
boosting RMSE 347 : 0.1485719 

forest 347 : -0.3898623 
forest mean 347 : -0.3848591 
forest RMSE 347 : 0.05488056 

nnet 347 : -0.4908099 
nnet mean 347 : -0.4155548 
nnet RMSE 347 : 0.1421825 


s: 348 
logit 348 : -0.5804986 
logit mean 348 : -0.4421663 
logit RMSE 348 : 0.07151186 

boosting 348 : -0.4592445 
boosting mean 348 : -0.4955079 
boosting RMSE 348 : 0.1483923 

forest 348 : -0.4238671 
forest mean 348 : -0.3849712 
forest RMSE 348 : 0.05481658 

nnet 348 : -0.4136089 
nnet mean 348 : -0.4155492 
nnet RMSE 348 : 0.1419800 


s: 349 
logit 349 : -0.3572247 
logit mean 349 : -0.4419229 
logit RMSE 349 : 0.07144604 

boosting 349 : -0.421037 
boosting mean 349 : -0.4952945 
boosting RMSE 349 : 0.1481838 

forest 349 : -0.3144259 
forest mean 349 : -0.384769 
forest RMSE 349 : 0.05492932 

nnet 349 : -0.2283083 
nnet mean 349 : -0.4150127 
nnet RMSE 349 : 0.1420740 


s: 350 
logit 350 : -0.4320406 
logit mean 350 : -0.4418947 
logit RMSE 350 : 0.07136445 

boosting 350 : -0.4344462 
boosting mean 350 : -0.4951206 
boosting RMSE 350 : 0.1479834 

forest 350 : -0.3141217 
forest mean 350 : -0.3845672 
forest RMSE 350 : 0.05504254 

nnet 350 : -0.4275696 
nnet mean 350 : -0.4150486 
nnet RMSE 350 : 0.1418785 


s: 351 
logit 351 : -0.4114461 
logit mean 351 : -0.4418079 
logit RMSE 351 : 0.07126534 

boosting 351 : -0.4796386 
boosting mean 351 : -0.4950765 
boosting RMSE 351 : 0.1478336 

forest 351 : -0.3463719 
forest mean 351 : -0.3844584 
forest RMSE 351 : 0.05503856 

nnet 351 : -0.2055519 
nnet mean 351 : -0.4144517 
nnet RMSE 351 : 0.1420559 


s: 352 
logit 352 : -0.3932096 
logit mean 352 : -0.4416699 
logit RMSE 352 : 0.07116496 

boosting 352 : -0.4620171 
boosting mean 352 : -0.4949826 
boosting RMSE 352 : 0.1476604 

forest 352 : -0.3530493 
forest mean 352 : -0.3843691 
forest RMSE 352 : 0.05501727 

nnet 352 : -0.7224242 
nnet mean 352 : -0.4153266 
nnet RMSE 352 : 0.1428912 


s: 353 
logit 353 : -0.5234587 
logit mean 353 : -0.4419016 
logit RMSE 353 : 0.07136724 

boosting 353 : -0.4479709 
boosting mean 353 : -0.4948494 
boosting RMSE 353 : 0.1474732 

forest 353 : -0.3901668 
forest mean 353 : -0.3843856 
forest RMSE 353 : 0.05494178 

nnet 353 : -0.5590236 
nnet mean 353 : -0.4157337 
nnet RMSE 353 : 0.1429395 


s: 354 
logit 354 : -0.3472678 
logit mean 354 : -0.4416342 
logit RMSE 354 : 0.07132146 

boosting 354 : -0.4779488 
boosting mean 354 : -0.4948017 
boosting RMSE 354 : 0.1473231 

forest 354 : -0.5128338 
forest mean 354 : -0.3847484 
forest RMSE 354 : 0.05519091 

nnet 354 : -0.4751844 
nnet mean 354 : -0.4159016 
nnet RMSE 354 : 0.1427933 


s: 355 
logit 355 : -0.4746796 
logit mean 355 : -0.4417273 
logit RMSE 355 : 0.07133114 

boosting 355 : -0.5020347 
boosting mean 355 : -0.494822 
boosting RMSE 355 : 0.1472151 

forest 355 : -0.3357632 
forest mean 355 : -0.3846104 
forest RMSE 355 : 0.05521847 

nnet 355 : -0.2573518 
nnet mean 355 : -0.415455 
nnet RMSE 355 : 0.1427929 


s: 356 
logit 356 : -0.5317912 
logit mean 356 : -0.4419803 
logit RMSE 356 : 0.07157254 

boosting 356 : -0.3342127 
boosting mean 356 : -0.4943709 
boosting RMSE 356 : 0.1470495 

forest 356 : -0.4624162 
forest mean 356 : -0.384829 
forest RMSE 356 : 0.05524001 

nnet 356 : -0.3251761 
nnet mean 356 : -0.4152014 
nnet RMSE 356 : 0.1426474 


s: 357 
logit 357 : -0.3996121 
logit mean 357 : -0.4418616 
logit RMSE 357 : 0.07147223 

boosting 357 : -0.4757147 
boosting mean 357 : -0.4943186 
boosting RMSE 357 : 0.1468981 

forest 357 : -0.4361532 
forest mean 357 : -0.3849727 
forest RMSE 357 : 0.05519576 

nnet 357 : -0.491325 
nnet mean 357 : -0.4154147 
nnet RMSE 357 : 0.1425294 


s: 358 
logit 358 : -0.4294351 
logit mean 358 : -0.4418269 
logit RMSE 358 : 0.07138929 

boosting 358 : -0.3904238 
boosting mean 358 : -0.4940284 
boosting RMSE 358 : 0.1466936 

forest 358 : -0.330521 
forest mean 358 : -0.3848206 
forest RMSE 358 : 0.0552408 

nnet 358 : -0.3658211 
nnet mean 358 : -0.4152761 
nnet RMSE 358 : 0.1423417 


s: 359 
logit 359 : -0.60699 
logit mean 359 : -0.442287 
logit RMSE 359 : 0.07212198 

boosting 359 : -0.6066044 
boosting mean 359 : -0.494342 
boosting RMSE 359 : 0.1468944 

forest 359 : -0.3823589 
forest mean 359 : -0.3848138 
forest RMSE 359 : 0.05517167 

nnet 359 : -0.3740526 
nnet mean 359 : -0.4151613 
nnet RMSE 359 : 0.1421499 


s: 360 
logit 360 : -0.4787794 
logit mean 360 : -0.4423884 
logit RMSE 360 : 0.07214132 

boosting 360 : -0.4702487 
boosting mean 360 : -0.4942751 
boosting RMSE 360 : 0.146737 

forest 360 : -0.4332986 
forest mean 360 : -0.3849485 
forest RMSE 360 : 0.05512293 

nnet 360 : -0.4603676 
nnet mean 360 : -0.4152869 
nnet RMSE 360 : 0.1419880 


s: 361 
logit 361 : -0.4799814 
logit mean 361 : -0.4424925 
logit RMSE 361 : 0.07216421 

boosting 361 : -0.637124 
boosting mean 361 : -0.4946708 
boosting RMSE 361 : 0.1470641 

forest 361 : -0.3469411 
forest mean 361 : -0.3848432 
forest RMSE 361 : 0.05511732 

nnet 361 : -0.6544943 
nnet mean 361 : -0.4159495 
nnet RMSE 361 : 0.1424224 


s: 362 
logit 362 : -0.4319054 
logit mean 362 : -0.4424633 
logit RMSE 362 : 0.07208398 

boosting 362 : -0.6636064 
boosting mean 362 : -0.4951375 
boosting RMSE 362 : 0.1475129 

forest 362 : -0.32525 
forest mean 362 : -0.3846786 
forest RMSE 362 : 0.05518118 

nnet 362 : -0.4994482 
nnet mean 362 : -0.4161802 
nnet RMSE 362 : 0.1423216 


s: 363 
logit 363 : -0.3931197 
logit mean 363 : -0.4423273 
logit RMSE 363 : 0.07198553 

boosting 363 : -0.4321147 
boosting mean 363 : -0.4949638 
boosting RMSE 363 : 0.1473193 

forest 363 : -0.2990011 
forest mean 363 : -0.3844425 
forest RMSE 363 : 0.05535951 

nnet 363 : -0.1044765 
nnet mean 363 : -0.4153215 
nnet RMSE 363 : 0.1429693 


s: 364 
logit 364 : -0.4282656 
logit mean 364 : -0.4422887 
logit RMSE 364 : 0.07190184 

boosting 364 : -0.3673087 
boosting mean 364 : -0.4946131 
boosting RMSE 364 : 0.1471267 

forest 364 : -0.4338693 
forest mean 364 : -0.3845783 
forest RMSE 364 : 0.05531191 

nnet 364 : -0.2732298 
nnet mean 364 : -0.4149311 
nnet RMSE 364 : 0.1429273 


s: 365 
logit 365 : -0.4703903 
logit mean 365 : -0.4423657 
logit RMSE 365 : 0.07189775 

boosting 365 : -0.4755449 
boosting mean 365 : -0.4945609 
boosting RMSE 365 : 0.1469783 

forest 365 : -0.2613402 
forest mean 365 : -0.3842407 
forest RMSE 365 : 0.05571087 

nnet 365 : -0.4568952 
nnet mean 365 : -0.4150461 
nnet RMSE 365 : 0.1427625 


s: 366 
logit 366 : -0.4635236 
logit mean 366 : -0.4424235 
logit RMSE 366 : 0.0718762 

boosting 366 : -0.526889 
boosting mean 366 : -0.4946492 
boosting RMSE 366 : 0.1469271 

forest 366 : -0.3609013 
forest mean 366 : -0.3841769 
forest RMSE 366 : 0.05567223 

nnet 366 : -0.3798098 
nnet mean 366 : -0.4149498 
nnet RMSE 366 : 0.1425712 


s: 367 
logit 367 : -0.3681613 
logit mean 367 : -0.4422211 
logit RMSE 367 : 0.07179744 

boosting 367 : -0.4456283 
boosting mean 367 : -0.4945157 
boosting RMSE 367 : 0.1467461 

forest 367 : -0.3143862 
forest mean 367 : -0.3839867 
forest RMSE 367 : 0.05577566 

nnet 367 : -0.3674848 
nnet mean 367 : -0.4148205 
nnet RMSE 367 : 0.1423870 


s: 368 
logit 368 : -0.4380002 
logit mean 368 : -0.4422097 
logit RMSE 368 : 0.07172718 

boosting 368 : -0.5707134 
boosting mean 368 : -0.4947227 
boosting RMSE 368 : 0.1468166 

forest 368 : -0.4436247 
forest mean 368 : -0.3841488 
forest RMSE 368 : 0.05574623 

nnet 368 : -0.1321719 
nnet mean 368 : -0.4140524 
nnet RMSE 368 : 0.1428771 


s: 369 
logit 369 : -0.3385464 
logit mean 369 : -0.4419287 
logit RMSE 369 : 0.07170133 

boosting 369 : -0.3327432 
boosting mean 369 : -0.4942837 
boosting RMSE 369 : 0.1466593 

forest 369 : -0.3639043 
forest mean 369 : -0.3840939 
forest RMSE 369 : 0.05570235 

nnet 369 : -0.4105317 
nnet mean 369 : -0.4140429 
nnet RMSE 369 : 0.1426845 


s: 370 
logit 370 : -0.3373621 
logit mean 370 : -0.4416461 
logit RMSE 370 : 0.07167838 

boosting 370 : -0.5493208 
boosting mean 370 : -0.4944325 
boosting RMSE 370 : 0.1466665 

forest 370 : -0.3350197 
forest mean 370 : -0.3839613 
forest RMSE 370 : 0.0557295 

nnet 370 : -0.2967445 
nnet mean 370 : -0.4137258 
nnet RMSE 370 : 0.1425926 


s: 371 
logit 371 : -0.3368446 
logit mean 371 : -0.4413636 
logit RMSE 371 : 0.07165677 

boosting 371 : -0.6208714 
boosting mean 371 : -0.4947733 
boosting RMSE 371 : 0.1469169 

forest 371 : -0.3534969 
forest mean 371 : -0.3838792 
forest RMSE 371 : 0.05570669 

nnet 371 : -0.5496134 
nnet mean 371 : -0.4140921 
nnet RMSE 371 : 0.1426120 


s: 372 
logit 372 : -0.435856 
logit mean 372 : -0.4413488 
logit RMSE 372 : 0.07158453 

boosting 372 : -0.7998791 
boosting mean 372 : -0.4955935 
boosting RMSE 372 : 0.1481770 

forest 372 : -0.3643344 
forest mean 372 : -0.3838267 
forest RMSE 372 : 0.05566249 

nnet 372 : -0.2928835 
nnet mean 372 : -0.4137663 
nnet RMSE 372 : 0.1425284 


s: 373 
logit 373 : -0.3437575 
logit mean 373 : -0.4410872 
logit RMSE 373 : 0.0715478 

boosting 373 : -0.2944485 
boosting mean 373 : -0.4950542 
boosting RMSE 373 : 0.1480791 

forest 373 : -0.3958387 
forest mean 373 : -0.3838589 
forest RMSE 373 : 0.05558824 

nnet 373 : -0.1690626 
nnet mean 373 : -0.4131102 
nnet RMSE 373 : 0.1428386 


s: 374 
logit 374 : -0.5033082 
logit mean 374 : -0.4412536 
logit RMSE 374 : 0.0716515 

boosting 374 : -0.3568954 
boosting mean 374 : -0.4946848 
boosting RMSE 374 : 0.1478978 

forest 374 : -0.4458401 
forest mean 374 : -0.3840246 
forest RMSE 374 : 0.05556446 

nnet 374 : -0.506621 
nnet mean 374 : -0.4133603 
nnet RMSE 374 : 0.1427540 


s: 375 
logit 375 : -0.4338585 
logit mean 375 : -0.4412338 
logit RMSE 375 : 0.07157725 

boosting 375 : -0.4728905 
boosting mean 375 : -0.4946267 
boosting RMSE 375 : 0.1477484 

forest 375 : -0.4113528 
forest mean 375 : -0.3840975 
forest RMSE 375 : 0.05549342 

nnet 375 : -0.4288021 
nnet mean 375 : -0.4134015 
nnet RMSE 375 : 0.1425713 


s: 376 
logit 376 : -0.4451147 
logit mean 376 : -0.4412442 
logit RMSE 376 : 0.07151986 

boosting 376 : -0.7487335 
boosting mean 376 : -0.4953025 
boosting RMSE 376 : 0.1486438 

forest 376 : -0.3801213 
forest mean 376 : -0.3840869 
forest RMSE 376 : 0.05542906 

nnet 376 : -0.2237743 
nnet mean 376 : -0.4128971 
nnet RMSE 376 : 0.1426714 


s: 377 
logit 377 : -0.5142513 
logit mean 377 : -0.4414378 
logit RMSE 377 : 0.07166692 

boosting 377 : -0.2126840 
boosting mean 377 : -0.4945529 
boosting RMSE 377 : 0.1487597 

forest 377 : -0.4102707 
forest mean 377 : -0.3841563 
forest RMSE 377 : 0.05535802 

nnet 377 : -0.2890884 
nnet mean 377 : -0.4125687 
nnet RMSE 377 : 0.1425965 


s: 378 
logit 378 : -0.5692808 
logit mean 378 : -0.441776 
logit RMSE 378 : 0.07209972 

boosting 378 : -0.3925713 
boosting mean 378 : -0.4942831 
boosting RMSE 378 : 0.1485633 

forest 378 : -0.4019727 
forest mean 378 : -0.3842035 
forest RMSE 378 : 0.05528484 

nnet 378 : -0.7068885 
nnet mean 378 : -0.4133473 
nnet RMSE 378 : 0.1432798 


s: 379 
logit 379 : -0.4075438 
logit mean 379 : -0.4416857 
logit RMSE 379 : 0.07200558 

boosting 379 : -0.4116342 
boosting mean 379 : -0.494065 
boosting RMSE 379 : 0.1483684 

forest 379 : -0.3952296 
forest mean 379 : -0.3842326 
forest RMSE 379 : 0.0552124 

nnet 379 : -0.5979081 
nnet mean 379 : -0.4138343 
nnet RMSE 379 : 0.1434514 


s: 380 
logit 380 : -0.3535511 
logit mean 380 : -0.4414538 
logit RMSE 380 : 0.07195024 

boosting 380 : -0.4353943 
boosting mean 380 : -0.4939106 
boosting RMSE 380 : 0.1481841 

forest 380 : -0.3163476 
forest mean 380 : -0.3840539 
forest RMSE 380 : 0.05530644 

nnet 380 : -0.6169633 
nnet mean 380 : -0.4143689 
nnet RMSE 380 : 0.1436942 


s: 381 
logit 381 : -0.4001861 
logit mean 381 : -0.4413455 
logit RMSE 381 : 0.07185575 

boosting 381 : -0.5915428 
boosting mean 381 : -0.4941668 
boosting RMSE 381 : 0.1483145 

forest 381 : -0.3397925 
forest mean 381 : -0.3839377 
forest RMSE 381 : 0.05531987 

nnet 381 : -0.2251549 
nnet mean 381 : -0.4138722 
nnet RMSE 381 : 0.1437848 


s: 382 
logit 382 : -0.4746886 
logit mean 382 : -0.4414327 
logit RMSE 382 : 0.07186331 

boosting 382 : -0.2991260 
boosting mean 382 : -0.4936563 
boosting RMSE 382 : 0.1482102 

forest 382 : -0.4793141 
forest mean 382 : -0.3841874 
forest RMSE 382 : 0.05539625 

nnet 382 : -0.4877036 
nnet mean 382 : -0.4140655 
nnet RMSE 382 : 0.1436665 


s: 383 
logit 383 : -0.3681393 
logit mean 383 : -0.4412414 
logit RMSE 383 : 0.0717879 

boosting 383 : -0.6793339 
boosting mean 383 : -0.4941411 
boosting RMSE 383 : 0.1487031 

forest 383 : -0.3496817 
forest mean 383 : -0.3840973 
forest RMSE 383 : 0.0553836 

nnet 383 : -0.3285763 
nnet mean 383 : -0.4138423 
nnet RMSE 383 : 0.1435253 


s: 384 
logit 384 : -0.4145622 
logit mean 384 : -0.4411719 
logit RMSE 384 : 0.07169821 

boosting 384 : -0.3330167 
boosting mean 384 : -0.4937215 
boosting RMSE 384 : 0.1485487 

forest 384 : -0.3765685 
forest mean 384 : -0.3840777 
forest RMSE 384 : 0.05532436 

nnet 384 : -0.5117052 
nnet mean 384 : -0.4140972 
nnet RMSE 384 : 0.1434516 


s: 385 
logit 385 : -0.5196318 
logit mean 385 : -0.4413757 
logit RMSE 385 : 0.07186414 

boosting 385 : -0.5445962 
boosting mean 385 : -0.4938536 
boosting RMSE 385 : 0.1485386 

forest 385 : -0.3262366 
forest mean 385 : -0.3839275 
forest RMSE 385 : 0.05538021 

nnet 385 : -0.7094659 
nnet mean 385 : -0.4148644 
nnet RMSE 385 : 0.1441307 


s: 386 
logit 386 : -0.405475 
logit mean 386 : -0.4412827 
logit RMSE 386 : 0.07177154 

boosting 386 : -0.3225198 
boosting mean 386 : -0.4934097 
boosting RMSE 386 : 0.1483985 

forest 386 : -0.4302924 
forest mean 386 : -0.3840476 
forest RMSE 386 : 0.05532991 

nnet 386 : -0.412606 
nnet mean 386 : -0.4148585 
nnet RMSE 386 : 0.1439453 


s: 387 
logit 387 : -0.4581327 
logit mean 387 : -0.4413262 
logit RMSE 387 : 0.07173964 

boosting 387 : -0.6486611 
boosting mean 387 : -0.4938109 
boosting RMSE 387 : 0.1487447 

forest 387 : -0.383519 
forest mean 387 : -0.3840462 
forest RMSE 387 : 0.05526473 

nnet 387 : -0.3201202 
nnet mean 387 : -0.4146137 
nnet RMSE 387 : 0.1438165 


s: 388 
logit 388 : -0.5096262 
logit mean 388 : -0.4415023 
logit RMSE 388 : 0.07186296 

boosting 388 : -0.7324846 
boosting mean 388 : -0.4944261 
boosting RMSE 388 : 0.1495087 

forest 388 : -0.3044732 
forest mean 388 : -0.3838411 
forest RMSE 388 : 0.05540612 

nnet 388 : -0.3263959 
nnet mean 388 : -0.4143863 
nnet RMSE 388 : 0.1436797 


s: 389 
logit 389 : -0.2776636 
logit mean 389 : -0.4410811 
logit RMSE 389 : 0.07203806 

boosting 389 : -0.5893429 
boosting mean 389 : -0.4946701 
boosting RMSE 389 : 0.1496247 

forest 389 : -0.5017675 
forest mean 389 : -0.3841443 
forest RMSE 389 : 0.0555749 

nnet 389 : -0.6782687 
nnet mean 389 : -0.4150647 
nnet RMSE 389 : 0.1441868 


s: 390 
logit 390 : -0.4003258 
logit mean 390 : -0.4409766 
logit RMSE 390 : 0.07194565 

boosting 390 : -0.5287303 
boosting mean 390 : -0.4947574 
boosting RMSE 390 : 0.1495749 

forest 390 : -0.4205918 
forest mean 390 : -0.3842378 
forest RMSE 390 : 0.0555134 

nnet 390 : -0.5108444 
nnet mean 390 : -0.4153103 
nnet RMSE 390 : 0.1441112 


s: 391 
logit 391 : -0.3082671 
logit mean 391 : -0.4406372 
logit RMSE 391 : 0.07200319 

boosting 391 : -0.2867547 
boosting mean 391 : -0.4942254 
boosting RMSE 391 : 0.1494932 

forest 391 : -0.3208387 
forest mean 391 : -0.3840756 
forest RMSE 391 : 0.05558672 

nnet 391 : -0.4804607 
nnet mean 391 : -0.4154769 
nnet RMSE 391 : 0.1439843 


s: 392 
logit 392 : -0.547409 
logit mean 392 : -0.4409095 
logit RMSE 392 : 0.07229569 

boosting 392 : -0.5377538 
boosting mean 392 : -0.4943365 
boosting RMSE 392 : 0.1494645 

forest 392 : -0.3535830 
forest mean 392 : -0.3839978 
forest RMSE 392 : 0.05556525 

nnet 392 : -0.2240166 
nnet mean 392 : -0.4149885 
nnet RMSE 392 : 0.1440750 


s: 393 
logit 393 : -0.5093863 
logit mean 393 : -0.4410838 
logit RMSE 393 : 0.07241418 

boosting 393 : -0.42632 
boosting mean 393 : -0.4941634 
boosting RMSE 393 : 0.1492801 

forest 393 : -0.3940976 
forest mean 393 : -0.3840235 
forest RMSE 393 : 0.05549531 

nnet 393 : -0.3063793 
nnet mean 393 : -0.4147121 
nnet RMSE 393 : 0.1439690 


s: 394 
logit 394 : -0.4221408 
logit mean 394 : -0.4410357 
logit RMSE 394 : 0.07233082 

boosting 394 : -0.4105945 
boosting mean 394 : -0.4939513 
boosting RMSE 394 : 0.1490915 

forest 394 : -0.3609579 
forest mean 394 : -0.383965 
forest RMSE 394 : 0.05545973 

nnet 394 : -0.6821177 
nnet mean 394 : -0.4153908 
nnet RMSE 394 : 0.1444870 


s: 395 
logit 395 : -0.410348 
logit mean 395 : -0.440958 
logit RMSE 395 : 0.07224108 

boosting 395 : -0.3268616 
boosting mean 395 : -0.4935283 
boosting RMSE 395 : 0.1489481 

forest 395 : -0.3810891 
forest mean 395 : -0.3839577 
forest RMSE 395 : 0.05539765 

nnet 395 : -0.4932739 
nnet mean 395 : -0.415588 
nnet RMSE 395 : 0.1443802 


s: 396 
logit 396 : -0.5442907 
logit mean 396 : -0.441219 
logit RMSE 396 : 0.07251325 

boosting 396 : -0.4621509 
boosting mean 396 : -0.493449 
boosting RMSE 396 : 0.1487927 

forest 396 : -0.3756354 
forest mean 396 : -0.3839367 
forest RMSE 396 : 0.05534121 

nnet 396 : -0.4347871 
nnet mean 396 : -0.4156365 
nnet RMSE 396 : 0.1442084 


s: 397 
logit 397 : -0.5411916 
logit mean 397 : -0.4414708 
logit RMSE 397 : 0.07276771 

boosting 397 : -0.3880811 
boosting mean 397 : -0.4931836 
boosting RMSE 397 : 0.1486064 

forest 397 : -0.4103546 
forest mean 397 : -0.3840032 
forest RMSE 397 : 0.05527391 

nnet 397 : -0.3349158 
nnet mean 397 : -0.4154332 
nnet RMSE 397 : 0.1440637 


s: 398 
logit 398 : -0.4510298 
logit mean 398 : -0.4414948 
logit RMSE 398 : 0.07272124 

boosting 398 : -0.5210124 
boosting mean 398 : -0.4932535 
boosting RMSE 398 : 0.1485435 

forest 398 : -0.4193711 
forest mean 398 : -0.3840921 
forest RMSE 398 : 0.05521296 

nnet 398 : -0.3553974 
nnet mean 398 : -0.4152823 
nnet RMSE 398 : 0.1439 


s: 399 
logit 399 : -0.4478434 
logit mean 399 : -0.4415107 
logit RMSE 399 : 0.07266954 

boosting 399 : -0.667446 
boosting mean 399 : -0.4936901 
boosting RMSE 399 : 0.1489602 

forest 399 : -0.4030982 
forest mean 399 : -0.3841397 
forest RMSE 399 : 0.05514395 

nnet 399 : -0.5629495 
nnet mean 399 : -0.4156524 
nnet RMSE 399 : 0.1439509 


s: 400 
logit 400 : -0.4616649 
logit mean 400 : -0.4415611 
logit RMSE 400 : 0.0726441 

boosting 400 : -0.3032703 
boosting mean 400 : -0.4932141 
boosting RMSE 400 : 0.1488525 

forest 400 : -0.4372078 
forest mean 400 : -0.3842724 
forest RMSE 400 : 0.05510639 

nnet 400 : -0.09992384 
nnet mean 400 : -0.4148631 
nnet RMSE 400 : 0.1445516 


s: 401 
logit 401 : -0.4562765 
logit mean 401 : -0.4415978 
logit RMSE 401 : 0.07260788 

boosting 401 : -0.5793809 
boosting mean 401 : -0.4934289 
boosting RMSE 401 : 0.1489364 

forest 401 : -0.3696695 
forest mean 401 : -0.384236 
forest RMSE 401 : 0.05505847 

nnet 401 : -0.4866629 
nnet mean 401 : -0.4150421 
nnet RMSE 401 : 0.1444361 


s: 402 
logit 402 : -0.3992105 
logit mean 402 : -0.4414923 
logit RMSE 402 : 0.07251752 

boosting 402 : -0.4828264 
boosting mean 402 : -0.4934026 
boosting RMSE 402 : 0.1488084 

forest 402 : -0.3682489 
forest mean 402 : -0.3841962 
forest RMSE 402 : 0.05501275 

nnet 402 : -0.2144724 
nnet mean 402 : -0.4145432 
nnet RMSE 402 : 0.1445528 


s: 403 
logit 403 : -0.2990376 
logit mean 403 : -0.4411389 
logit RMSE 403 : 0.0726019 

boosting 403 : -0.4059475 
boosting mean 403 : -0.4931856 
boosting RMSE 403 : 0.1486239 

forest 403 : -0.3364946 
forest mean 403 : -0.3840778 
forest RMSE 403 : 0.05503544 

nnet 403 : -0.3643008 
nnet mean 403 : -0.4144185 
nnet RMSE 403 : 0.1443843 


s: 404 
logit 404 : -0.564982 
logit mean 404 : -0.4414454 
logit RMSE 404 : 0.07297508 

boosting 404 : -0.5381006 
boosting mean 404 : -0.4932967 
boosting RMSE 404 : 0.1485988 

forest 404 : -0.4294737 
forest mean 404 : -0.3841902 
forest RMSE 404 : 0.05498684 

nnet 404 : -0.7416516 
nnet mean 404 : -0.4152285 
nnet RMSE 404 : 0.1452038 


s: 405 
logit 405 : -0.3719066 
logit mean 405 : -0.4412737 
logit RMSE 405 : 0.0728983 

boosting 405 : -0.3582526 
boosting mean 405 : -0.4929633 
boosting RMSE 405 : 0.1484297 

forest 405 : -0.4105820 
forest mean 405 : -0.3842554 
forest RMSE 405 : 0.05492143 

nnet 405 : -0.3757257 
nnet mean 405 : -0.415131 
nnet RMSE 405 : 0.1450295 


s: 406 
logit 406 : -0.4474442 
logit mean 406 : -0.4412889 
logit RMSE 406 : 0.07284653 

boosting 406 : -0.6980516 
boosting mean 406 : -0.4934684 
boosting RMSE 406 : 0.1489830 

forest 406 : -0.3707033 
forest mean 406 : -0.384222 
forest RMSE 406 : 0.05487302 

nnet 406 : -0.2756696 
nnet mean 406 : -0.4147875 
nnet RMSE 406 : 0.1449821 


s: 407 
logit 407 : -0.465399 
logit mean 407 : -0.4413481 
logit RMSE 407 : 0.07282917 

boosting 407 : -0.6444004 
boosting mean 407 : -0.4938393 
boosting RMSE 407 : 0.1492922 

forest 407 : -0.3394762 
forest mean 407 : -0.3841121 
forest RMSE 407 : 0.05488762 

nnet 407 : -0.6151723 
nnet mean 407 : -0.4152798 
nnet RMSE 407 : 0.1451962 


s: 408 
logit 408 : -0.4144973 
logit mean 408 : -0.4412823 
logit RMSE 408 : 0.0727434 

boosting 408 : -0.5080607 
boosting mean 408 : -0.4938741 
boosting RMSE 408 : 0.1492050 

forest 408 : -0.4348752 
forest mean 408 : -0.3842365 
forest RMSE 408 : 0.0548475 

nnet 408 : -0.3553637 
nnet mean 408 : -0.415133 
nnet RMSE 408 : 0.1450350 


s: 409 
logit 409 : -0.3791006 
logit mean 409 : -0.4411303 
logit RMSE 409 : 0.07266177 

boosting 409 : -0.4249595 
boosting mean 409 : -0.4937056 
boosting RMSE 409 : 0.1490276 

forest 409 : -0.452283 
forest mean 409 : -0.3844028 
forest RMSE 409 : 0.05484137 

nnet 409 : -0.2697377 
nnet mean 409 : -0.4147775 
nnet RMSE 409 : 0.1450007 


s: 410 
logit 410 : -0.4401957 
logit mean 410 : -0.441128 
logit RMSE 410 : 0.07260025 

boosting 410 : -0.4745402 
boosting mean 410 : -0.4936589 
boosting RMSE 410 : 0.1488913 

forest 410 : -0.3916919 
forest mean 410 : -0.3844206 
forest RMSE 410 : 0.05477599 

nnet 410 : -0.3187689 
nnet mean 410 : -0.4145433 
nnet RMSE 410 : 0.1448793 


s: 411 
logit 411 : -0.415749 
logit mean 411 : -0.4410663 
logit RMSE 411 : 0.07251603 

boosting 411 : -0.3799574 
boosting mean 411 : -0.4933822 
boosting RMSE 411 : 0.1487133 

forest 411 : -0.444667 
forest mean 411 : -0.3845672 
forest RMSE 411 : 0.05475366 

nnet 411 : -0.3523547 
nnet mean 411 : -0.414392 
nnet RMSE 411 : 0.1447220 


s: 412 
logit 412 : -0.4649712 
logit mean 412 : -0.4411243 
logit RMSE 412 : 0.07249867 

boosting 412 : -0.5106883 
boosting mean 412 : -0.4934243 
boosting RMSE 412 : 0.1486328 

forest 412 : -0.2957639 
forest mean 412 : -0.3843517 
forest RMSE 412 : 0.05492775 

nnet 412 : -0.2648337 
nnet mean 412 : -0.414029 
nnet RMSE 412 : 0.1446996 


s: 413 
logit 413 : -0.3815078 
logit mean 413 : -0.4409799 
logit RMSE 413 : 0.07241656 

boosting 413 : -0.5072651 
boosting mean 413 : -0.4934578 
boosting RMSE 413 : 0.1485466 

forest 413 : -0.4313383 
forest mean 413 : -0.3844654 
forest RMSE 413 : 0.05488288 

nnet 413 : -0.2386662 
nnet mean 413 : -0.4136044 
nnet RMSE 413 : 0.1447422 


s: 414 
logit 414 : -0.3996187 
logit mean 414 : -0.44088 
logit RMSE 414 : 0.07232905 

boosting 414 : -0.6340887 
boosting mean 414 : -0.4937975 
boosting RMSE 414 : 0.1488124 

forest 414 : -0.4569631 
forest mean 414 : -0.3846406 
forest RMSE 414 : 0.054888 

nnet 414 : -0.3304505 
nnet mean 414 : -0.4134035 
nnet RMSE 414 : 0.1446077 


s: 415 
logit 415 : -0.4610054 
logit mean 415 : -0.4409285 
logit RMSE 415 : 0.0723039 

boosting 415 : -0.5719924 
boosting mean 415 : -0.4939859 
boosting RMSE 415 : 0.1488726 

forest 415 : -0.3373437 
forest mean 415 : -0.3845266 
forest RMSE 415 : 0.05490804 

nnet 415 : -0.3047151 
nnet mean 415 : -0.4131416 
nnet RMSE 415 : 0.1445090 


s: 416 
logit 416 : -0.4439068 
logit mean 416 : -0.4409357 
logit RMSE 416 : 0.07224902 

boosting 416 : -0.4894474 
boosting mean 416 : -0.493975 
boosting RMSE 416 : 0.1487582 

forest 416 : -0.3106083 
forest mean 416 : -0.3843489 
forest RMSE 416 : 0.05501686 

nnet 416 : -0.5413892 
nnet mean 416 : -0.4134499 
nnet RMSE 416 : 0.1445016 


s: 417 
logit 417 : -0.4421698 
logit mean 417 : -0.4409386 
logit RMSE 417 : 0.07219188 

boosting 417 : -0.6964475 
boosting mean 417 : -0.4944605 
boosting RMSE 417 : 0.1492873 

forest 417 : -0.4112338 
forest mean 417 : -0.3844134 
forest RMSE 417 : 0.0549536 

nnet 417 : -0.3610887 
nnet mean 417 : -0.4133244 
nnet RMSE 417 : 0.1443408 


s: 418 
logit 418 : -0.4800433 
logit mean 418 : -0.4410322 
logit RMSE 418 : 0.07221168 

boosting 418 : -0.5695722 
boosting mean 418 : -0.4946402 
boosting RMSE 418 : 0.1493391 

forest 418 : -0.3791926 
forest mean 418 : -0.3844009 
forest RMSE 418 : 0.05489726 

nnet 418 : -0.538082 
nnet mean 418 : -0.4136228 
nnet RMSE 418 : 0.1443262 


s: 419 
logit 419 : -0.5473691 
logit mean 419 : -0.441286 
logit RMSE 419 : 0.07248389 

boosting 419 : -0.5774205 
boosting mean 419 : -0.4948378 
boosting RMSE 419 : 0.1494124 

forest 419 : -0.4296889 
forest mean 419 : -0.384509 
forest RMSE 419 : 0.0548509 

nnet 419 : -0.5520278 
nnet mean 419 : -0.4139531 
nnet RMSE 419 : 0.1443451 


s: 420 
logit 420 : -0.4337855 
logit mean 420 : -0.4412681 
logit RMSE 420 : 0.07241631 

boosting 420 : -0.6538192 
boosting mean 420 : -0.4952163 
boosting RMSE 420 : 0.1497475 

forest 420 : -0.4058755 
forest mean 420 : -0.3845598 
forest RMSE 420 : 0.05478631 

nnet 420 : -0.3540127 
nnet mean 420 : -0.4138104 
nnet RMSE 420 : 0.1441906 


s: 421 
logit 421 : -0.4688537 
logit mean 421 : -0.4413337 
logit RMSE 421 : 0.07240806 

boosting 421 : -0.4257349 
boosting mean 421 : -0.4950513 
boosting RMSE 421 : 0.1495748 

forest 421 : -0.2980495 
forest mean 421 : -0.3843543 
forest RMSE 421 : 0.05494632 

nnet 421 : -0.3102293 
nnet mean 421 : -0.4135644 
nnet RMSE 421 : 0.1440857 


s: 422 
logit 422 : -0.4749632 
logit mean 422 : -0.4414133 
logit RMSE 422 : 0.07241422 

boosting 422 : -0.5334807 
boosting mean 422 : -0.4951423 
boosting RMSE 422 : 0.1495387 

forest 422 : -0.3838897 
forest mean 422 : -0.3843532 
forest RMSE 422 : 0.05488679 

nnet 422 : -0.3290236 
nnet mean 422 : -0.4133641 
nnet RMSE 422 : 0.1439563 


s: 423 
logit 423 : -0.4624376 
logit mean 423 : -0.441463 
logit RMSE 423 : 0.07239226 

boosting 423 : -0.5990356 
boosting mean 423 : -0.4953879 
boosting RMSE 423 : 0.149675 

forest 423 : -0.4627694 
forest mean 423 : -0.3845386 
forest RMSE 423 : 0.05490676 

nnet 423 : -0.5364605 
nnet mean 423 : -0.4136551 
nnet RMSE 423 : 0.1439391 


s: 424 
logit 424 : -0.5247871 
logit mean 424 : -0.4416596 
logit RMSE 424 : 0.07256035 

boosting 424 : -0.5305911 
boosting mean 424 : -0.495471 
boosting RMSE 424 : 0.1496329 

forest 424 : -0.4023117 
forest mean 424 : -0.3845805 
forest RMSE 424 : 0.05484208 

nnet 424 : -0.1200681 
nnet mean 424 : -0.4129626 
nnet RMSE 424 : 0.1444105 


s: 425 
logit 425 : -0.3517892 
logit mean 425 : -0.4414481 
logit RMSE 425 : 0.07251266 

boosting 425 : -0.6253478 
boosting mean 425 : -0.4957766 
boosting RMSE 425 : 0.1498559 

forest 425 : -0.3797099 
forest mean 425 : -0.3845691 
forest RMSE 425 : 0.05478637 

nnet 425 : -0.2159952 
nnet mean 425 : -0.4124992 
nnet RMSE 425 : 0.1445164 


s: 426 
logit 426 : -0.5291235 
logit mean 426 : -0.4416539 
logit RMSE 426 : 0.07269719 

boosting 426 : -0.4700705 
boosting mean 426 : -0.4957162 
boosting RMSE 426 : 0.1497184 

forest 426 : -0.4166851 
forest mean 426 : -0.3846445 
forest RMSE 426 : 0.054728 

nnet 426 : -0.2696695 
nnet mean 426 : -0.4121639 
nnet RMSE 426 : 0.1444848 


s: 427 
logit 427 : -0.4785345 
logit mean 427 : -0.4417403 
logit RMSE 427 : 0.0727114 

boosting 427 : -0.3018414 
boosting mean 427 : -0.4952622 
boosting RMSE 427 : 0.1496184 

forest 427 : -0.3045252 
forest mean 427 : -0.3844568 
forest RMSE 427 : 0.05485879 

nnet 427 : -0.5382995 
nnet mean 427 : -0.4124593 
nnet RMSE 427 : 0.1444706 


s: 428 
logit 428 : -0.4624735 
logit mean 428 : -0.4417887 
logit RMSE 428 : 0.07268916 

boosting 428 : -0.3941097 
boosting mean 428 : -0.4950258 
boosting RMSE 428 : 0.1494438 

forest 428 : -0.3233997 
forest mean 428 : -0.3843142 
forest RMSE 428 : 0.05491962 

nnet 428 : -0.186288 
nnet mean 428 : -0.4119309 
nnet RMSE 428 : 0.144671 


s: 429 
logit 429 : -0.4469456 
logit mean 429 : -0.4418007 
logit RMSE 429 : 0.07263977 

boosting 429 : -0.4714466 
boosting mean 429 : -0.4949709 
boosting RMSE 429 : 0.1493094 

forest 429 : -0.3056271 
forest mean 429 : -0.3841308 
forest RMSE 429 : 0.05504448 

nnet 429 : -0.4838426 
nnet mean 429 : -0.4120985 
nnet RMSE 429 : 0.1445590 


s: 430 
logit 430 : -0.3571082 
logit mean 430 : -0.4416038 
logit RMSE 430 : 0.07258473 

boosting 430 : -0.5463324 
boosting mean 430 : -0.4950903 
boosting RMSE 430 : 0.1493025 

forest 430 : -0.3133579 
forest mean 430 : -0.3839662 
forest RMSE 430 : 0.05513897 

nnet 430 : -0.3863013 
nnet mean 430 : -0.4120385 
nnet RMSE 430 : 0.1443923 


s: 431 
logit 431 : -0.4733259 
logit mean 431 : -0.4416774 
logit RMSE 431 : 0.07258646 

boosting 431 : -0.559843 
boosting mean 431 : -0.4952406 
boosting RMSE 431 : 0.1493279 

forest 431 : -0.4091395 
forest mean 431 : -0.3840246 
forest RMSE 431 : 0.05507673 

nnet 431 : -0.6202983 
nnet mean 431 : -0.4125217 
nnet RMSE 431 : 0.1446145 


s: 432 
logit 432 : -0.4441282 
logit mean 432 : -0.4416831 
logit RMSE 432 : 0.07253348 

boosting 432 : -0.4844768 
boosting mean 432 : -0.4952156 
boosting RMSE 432 : 0.1492103 

forest 432 : -0.3405367 
forest mean 432 : -0.3839239 
forest RMSE 432 : 0.05508728 

nnet 432 : -0.362895 
nnet mean 432 : -0.4124068 
nnet RMSE 432 : 0.1444581 


s: 433 
logit 433 : -0.4826119 
logit mean 433 : -0.4417776 
logit RMSE 433 : 0.07255836 

boosting 433 : -0.4781484 
boosting mean 433 : -0.4951762 
boosting RMSE 433 : 0.1490852 

forest 433 : -0.3565233 
forest mean 433 : -0.3838606 
forest RMSE 433 : 0.05506329 

nnet 433 : -0.3626747 
nnet mean 433 : -0.412292 
nnet RMSE 433 : 0.1443023 


s: 434 
logit 434 : -0.4542346 
logit mean 434 : -0.4418063 
logit RMSE 434 : 0.07252147 

boosting 434 : -0.4610748 
boosting mean 434 : -0.4950976 
boosting RMSE 434 : 0.1489422 

forest 434 : -0.3915787 
forest mean 434 : -0.3838784 
forest RMSE 434 : 0.0550013 

nnet 434 : -0.565824 
nnet mean 434 : -0.4126457 
nnet RMSE 434 : 0.1443556 


s: 435 
logit 435 : -0.4364632 
logit mean 435 : -0.441794 
logit RMSE 435 : 0.07245915 

boosting 435 : -0.4773423 
boosting mean 435 : -0.4950568 
boosting RMSE 435 : 0.1488171 

forest 435 : -0.431832 
forest mean 435 : -0.3839887 
forest RMSE 435 : 0.05495924 

nnet 435 : -0.5865328 
nnet mean 435 : -0.4130455 
nnet RMSE 435 : 0.1444667 


s: 436 
logit 436 : -0.3470359 
logit mean 436 : -0.4415767 
logit RMSE 436 : 0.07242044 

boosting 436 : -0.3277308 
boosting mean 436 : -0.4946731 
boosting RMSE 436 : 0.1486866 

forest 436 : -0.4153907 
forest mean 436 : -0.3840607 
forest RMSE 436 : 0.05490113 

nnet 436 : -0.4818945 
nnet mean 436 : -0.4132034 
nnet RMSE 436 : 0.1443542 


s: 437 
logit 437 : -0.4859083 
logit mean 437 : -0.4416781 
logit RMSE 437 : 0.07245418 

boosting 437 : -0.6021488 
boosting mean 437 : -0.494919 
boosting RMSE 437 : 0.1488309 

forest 437 : -0.3711536 
forest mean 437 : -0.3840311 
forest RMSE 437 : 0.05485563 

nnet 437 : -0.3495805 
nnet mean 437 : -0.4130578 
nnet RMSE 437 : 0.1442091 


s: 438 
logit 438 : -0.4487976 
logit mean 438 : -0.4416944 
logit RMSE 438 : 0.07240897 

boosting 438 : -0.6024391 
boosting mean 438 : -0.4951645 
boosting RMSE 438 : 0.1489753 

forest 438 : -0.3580615 
forest mean 438 : -0.3839719 
forest RMSE 438 : 0.05482961 

nnet 438 : -0.5157593 
nnet mean 438 : -0.4132923 
nnet RMSE 438 : 0.1441506 


s: 439 
logit 439 : -0.3993444 
logit mean 439 : -0.4415979 
logit RMSE 439 : 0.07232646 

boosting 439 : -0.426307 
boosting mean 439 : -0.4950076 
boosting RMSE 439 : 0.1488108 

forest 439 : -0.3671842 
forest mean 439 : -0.3839336 
forest RMSE 439 : 0.05478951 

nnet 439 : -0.3406668 
nnet mean 439 : -0.4131268 
nnet RMSE 439 : 0.1440141 


s: 440 
logit 440 : -0.4438329 
logit mean 440 : -0.441603 
logit RMSE 440 : 0.07227444 

boosting 440 : -0.4736803 
boosting mean 440 : -0.4949592 
boosting RMSE 440 : 0.1486831 

forest 440 : -0.373657 
forest mean 440 : -0.3839103 
forest RMSE 440 : 0.05474163 

nnet 440 : -0.3303103 
nnet mean 440 : -0.4129386 
nnet RMSE 440 : 0.1438887 


s: 441 
logit 441 : -0.502346 
logit mean 441 : -0.4417407 
logit RMSE 441 : 0.07235677 

boosting 441 : -0.612955 
boosting mean 441 : -0.4952267 
boosting RMSE 441 : 0.1488602 

forest 441 : -0.3647417 
forest mean 441 : -0.3838668 
forest RMSE 441 : 0.0547053 

nnet 441 : -0.5252029 
nnet mean 441 : -0.4131932 
nnet RMSE 441 : 0.1438491 


s: 442 
logit 442 : -0.4296101 
logit mean 442 : -0.4417133 
logit RMSE 442 : 0.07228859 

boosting 442 : -0.6050351 
boosting mean 442 : -0.4954752 
boosting RMSE 442 : 0.1490112 

forest 442 : -0.3336266 
forest mean 442 : -0.3837531 
forest RMSE 442 : 0.0547345 

nnet 442 : -0.3670523 
nnet mean 442 : -0.4130888 
nnet RMSE 442 : 0.1436949 


s: 443 
logit 443 : -0.4510637 
logit mean 443 : -0.4417344 
logit RMSE 443 : 0.0722477 

boosting 443 : -0.4126831 
boosting mean 443 : -0.4952883 
boosting RMSE 443 : 0.1488442 

forest 443 : -0.3407087 
forest mean 443 : -0.3836560 
forest RMSE 443 : 0.05474522 

nnet 443 : -0.4184971 
nnet mean 443 : -0.413101 
nnet RMSE 443 : 0.1435353 


s: 444 
logit 444 : -0.3819019 
logit mean 444 : -0.4415996 
logit RMSE 444 : 0.0721714 

boosting 444 : -0.5281712 
boosting mean 444 : -0.4953623 
boosting RMSE 444 : 0.1488008 

forest 444 : -0.3823823 
forest mean 444 : -0.3836531 
forest RMSE 444 : 0.05468992 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 444 : -0.1755896 
nnet mean 444 : -0.4125661 
nnet RMSE 444 : 0.1437685 


s: 445 
logit 445 : -0.4054594 
logit mean 445 : -0.4415184 
logit RMSE 445 : 0.07209073 

boosting 445 : -0.5034547 
boosting mean 445 : -0.4953805 
boosting RMSE 445 : 0.1487144 

forest 445 : -0.4340057 
forest mean 445 : -0.3837662 
forest RMSE 445 : 0.05465222 

nnet 445 : -0.577872 
nnet mean 445 : -0.4129375 
nnet RMSE 445 : 0.1438542 


s: 446 
logit 446 : -0.3547478 
logit mean 446 : -0.4413239 
logit RMSE 446 : 0.07204174 

boosting 446 : -0.5997794 
boosting mean 446 : -0.4956146 
boosting RMSE 446 : 0.1488485 

forest 446 : -0.4301981 
forest mean 446 : -0.3838704 
forest RMSE 446 : 0.05460964 

nnet 446 : -0.4383478 
nnet mean 446 : -0.4129945 
nnet RMSE 446 : 0.1437044 


s: 447 
logit 447 : -0.3325469 
logit mean 447 : -0.4410805 
logit RMSE 447 : 0.0720318 

boosting 447 : -0.5838678 
boosting mean 447 : -0.495812 
boosting RMSE 447 : 0.1489361 

forest 447 : -0.4233062 
forest mean 447 : -0.3839586 
forest RMSE 447 : 0.05455966 

nnet 447 : -0.3567118 
nnet mean 447 : -0.4128686 
nnet RMSE 447 : 0.1435581 


s: 448 
logit 448 : -0.4992698 
logit mean 448 : -0.4412104 
logit RMSE 448 : 0.07210406 

boosting 448 : -0.4612938 
boosting mean 448 : -0.495735 
boosting RMSE 448 : 0.1487979 

forest 448 : -0.3705789 
forest mean 448 : -0.3839287 
forest RMSE 448 : 0.05451645 

nnet 448 : -0.4617152 
nnet mean 448 : -0.4129776 
nnet RMSE 448 : 0.1434275 


s: 449 
logit 449 : -0.4332824 
logit mean 449 : -0.4411927 
logit RMSE 449 : 0.07204085 

boosting 449 : -0.7111913 
boosting mean 449 : -0.4962148 
boosting RMSE 449 : 0.1493559 

forest 449 : -0.3257795 
forest mean 449 : -0.3837992 
forest RMSE 449 : 0.05456824 

nnet 449 : -0.2791377 
nnet mean 449 : -0.4126796 
nnet RMSE 449 : 0.1433811 


s: 450 
logit 450 : -0.4694657 
logit mean 450 : -0.4412556 
logit RMSE 450 : 0.07203523 

boosting 450 : -0.6987185 
boosting mean 450 : -0.4966648 
boosting RMSE 450 : 0.1498530 

forest 450 : -0.3835949 
forest mean 450 : -0.3837987 
forest RMSE 450 : 0.05451306 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 450 : -0.1199157 
nnet mean 450 : -0.412029 
nnet RMSE 450 : 0.1438290 


s: 451 
logit 451 : -0.3844426 
logit mean 451 : -0.4411296 
logit RMSE 451 : 0.07195905 

boosting 451 : -0.4949393 
boosting mean 451 : -0.496661 
boosting RMSE 451 : 0.1497535 

forest 451 : -0.4059136 
forest mean 451 : -0.3838478 
forest RMSE 451 : 0.05445331 

nnet 451 : -0.3681722 
nnet mean 451 : -0.4119317 
nnet RMSE 451 : 0.1436773 


s: 452 
logit 452 : -0.3621980 
logit mean 452 : -0.440955 
logit RMSE 452 : 0.07190139 

boosting 452 : -0.5019176 
boosting mean 452 : -0.4966726 
boosting RMSE 452 : 0.1496645 

forest 452 : -0.4448201 
forest mean 452 : -0.3839827 
forest RMSE 452 : 0.05443388 

nnet 452 : -0.364151 
nnet mean 452 : -0.411826 
nnet RMSE 452 : 0.1435282 


s: 453 
logit 453 : -0.4475506 
logit mean 453 : -0.4409695 
logit RMSE 453 : 0.07185673 

boosting 453 : -0.4761341 
boosting mean 453 : -0.4966273 
boosting RMSE 453 : 0.1495420 

forest 453 : -0.5254957 
forest mean 453 : -0.3842951 
forest RMSE 453 : 0.05469253 

nnet 453 : -0.4851497 
nnet mean 453 : -0.4119879 
nnet RMSE 453 : 0.1434255 


s: 454 
logit 454 : -0.3805852 
logit mean 454 : -0.4408365 
logit RMSE 454 : 0.07178333 

boosting 454 : -0.3004677 
boosting mean 454 : -0.4961952 
boosting RMSE 454 : 0.1494503 

forest 454 : -0.2183453 
forest mean 454 : -0.3839295 
forest RMSE 454 : 0.05529347 

nnet 454 : -0.3491263 
nnet mean 454 : -0.4118494 
nnet RMSE 454 : 0.1432874 


s: 455 
logit 455 : -0.4310091 
logit mean 455 : -0.4408149 
logit RMSE 455 : 0.07171914 

boosting 455 : -0.3717948 
boosting mean 455 : -0.4959218 
boosting RMSE 455 : 0.1492918 

forest 455 : -0.4604597 
forest mean 455 : -0.3840977 
forest RMSE 455 : 0.05530535 

nnet 455 : -0.3777258 
nnet mean 455 : -0.4117744 
nnet RMSE 455 : 0.1431336 


s: 456 
logit 456 : -0.3911822 
logit mean 456 : -0.4407061 
logit RMSE 456 : 0.07164164 

boosting 456 : -0.3789241 
boosting mean 456 : -0.4956653 
boosting RMSE 456 : 0.1491313 

forest 456 : -0.3900607 
forest mean 456 : -0.3841108 
forest RMSE 456 : 0.05524664 

nnet 456 : -0.5338578 
nnet mean 456 : -0.4120421 
nnet RMSE 456 : 0.1431139 


s: 457 
logit 457 : -0.3665073 
logit mean 457 : -0.4405437 
logit RMSE 457 : 0.07158037 

boosting 457 : -0.4138026 
boosting mean 457 : -0.4954861 
boosting RMSE 457 : 0.1489694 

forest 457 : -0.4468454 
forest mean 457 : -0.3842481 
forest RMSE 457 : 0.05522965 

nnet 457 : -0.3154582 
nnet mean 457 : -0.4118308 
nnet RMSE 457 : 0.1430120 


s: 458 
logit 458 : -0.4294839 
logit mean 458 : -0.4405196 
logit RMSE 458 : 0.07151545 

boosting 458 : -0.3016153 
boosting mean 458 : -0.4950628 
boosting RMSE 458 : 0.1488777 

forest 458 : -0.3908662 
forest mean 458 : -0.3842625 
forest RMSE 458 : 0.05517097 

nnet 458 : -0.3729550 
nnet mean 458 : -0.4117459 
nnet RMSE 458 : 0.1428613 


s: 459 
logit 459 : -0.4726767 
logit mean 459 : -0.4405896 
logit RMSE 459 : 0.071518 

boosting 459 : -0.3805380 
boosting mean 459 : -0.4948133 
boosting RMSE 459 : 0.1487182 

forest 459 : -0.4941265 
forest mean 459 : -0.3845019 
forest RMSE 459 : 0.05528568 

nnet 459 : -0.2562031 
nnet mean 459 : -0.4114070 
nnet RMSE 459 : 0.1428634 


s: 460 
logit 460 : -0.4628416 
logit mean 460 : -0.440638 
logit RMSE 460 : 0.07150028 

boosting 460 : -0.5581085 
boosting mean 460 : -0.4949509 
boosting RMSE 460 : 0.1487393 

forest 460 : -0.4135245 
forest mean 460 : -0.384565 
forest RMSE 460 : 0.05522916 

nnet 460 : -0.5991883 
nnet mean 460 : -0.4118153 
nnet RMSE 460 : 0.1430099 


s: 461 
logit 461 : -0.3435493 
logit mean 461 : -0.4404274 
logit RMSE 461 : 0.07147107 

boosting 461 : -0.6666675 
boosting mean 461 : -0.4953234 
boosting RMSE 461 : 0.1490961 

forest 461 : -0.3239815 
forest mean 461 : -0.3844336 
forest RMSE 461 : 0.05528272 

nnet 461 : -0.7893231 
nnet mean 461 : -0.4126342 
nnet RMSE 461 : 0.1440009 


s: 462 
logit 462 : -0.4320915 
logit mean 462 : -0.4404094 
logit RMSE 462 : 0.07140928 

boosting 462 : -0.4692135 
boosting mean 462 : -0.4952669 
boosting RMSE 462 : 0.1489694 

forest 462 : -0.3839783 
forest mean 462 : -0.3844326 
forest RMSE 462 : 0.05522788 

nnet 462 : -0.3547432 
nnet mean 462 : -0.4125088 
nnet RMSE 462 : 0.1438604 


s: 463 
logit 463 : -0.4968752 
logit mean 463 : -0.4405313 
logit RMSE 463 : 0.07147406 

boosting 463 : -0.4998883 
boosting mean 463 : -0.4952769 
boosting RMSE 463 : 0.1488809 

forest 463 : -0.339799 
forest mean 463 : -0.3843362 
forest RMSE 463 : 0.05523911 

nnet 463 : -0.5562905 
nnet mean 463 : -0.4128194 
nnet RMSE 463 : 0.1438884 


s: 464 
logit 464 : -0.4668714 
logit mean 464 : -0.4405881 
logit RMSE 464 : 0.07146446 

boosting 464 : -0.533276 
boosting mean 464 : -0.4953588 
boosting RMSE 464 : 0.148849 

forest 464 : -0.3995921 
forest mean 464 : -0.3843691 
forest RMSE 464 : 0.05517955 

nnet 464 : -0.3524661 
nnet mean 464 : -0.4126893 
nnet RMSE 464 : 0.1437502 


s: 465 
logit 465 : -0.4076335 
logit mean 465 : -0.4405172 
logit RMSE 465 : 0.07138846 

boosting 465 : -0.3434803 
boosting mean 465 : -0.4950321 
boosting RMSE 465 : 0.1487119 

forest 465 : -0.3823411 
forest mean 465 : -0.3843647 
forest RMSE 465 : 0.05512627 

nnet 465 : -0.2596064 
nnet mean 465 : -0.4123601 
nnet RMSE 465 : 0.1437430 


s: 466 
logit 466 : -0.4350511 
logit mean 466 : -0.4405055 
logit RMSE 466 : 0.0713303 

boosting 466 : -0.5783885 
boosting mean 466 : -0.495211 
boosting RMSE 466 : 0.1487820 

forest 466 : -0.3706669 
forest mean 466 : -0.3843353 
forest RMSE 466 : 0.05508386 

nnet 466 : -0.4163151 
nnet mean 466 : -0.4123686 
nnet RMSE 466 : 0.1435907 


s: 467 
logit 467 : -0.462418 
logit mean 467 : -0.4405524 
logit RMSE 467 : 0.0713124 

boosting 467 : -0.3607778 
boosting mean 467 : -0.4949232 
boosting RMSE 467 : 0.1486337 

forest 467 : -0.3870552 
forest mean 467 : -0.3843411 
forest RMSE 467 : 0.05502811 

nnet 467 : -0.4264156 
nnet mean 467 : -0.4123987 
nnet RMSE 467 : 0.1434421 


s: 468 
logit 468 : -0.4357451 
logit mean 468 : -0.4405421 
logit RMSE 468 : 0.07125534 

boosting 468 : -0.4707898 
boosting mean 468 : -0.4948716 
boosting RMSE 468 : 0.1485108 

forest 468 : -0.3695928 
forest mean 468 : -0.3843096 
forest RMSE 468 : 0.05498725 

nnet 468 : -0.3904864 
nnet mean 468 : -0.4123519 
nnet RMSE 468 : 0.1432894 


s: 469 
logit 469 : -0.4782493 
logit mean 469 : -0.4406225 
logit RMSE 469 : 0.07127098 

boosting 469 : -0.4720145 
boosting mean 469 : -0.4948228 
boosting RMSE 469 : 0.1483897 

forest 469 : -0.394914 
forest mean 469 : -0.3843322 
forest RMSE 469 : 0.0549291 

nnet 469 : -0.562568 
nnet mean 469 : -0.4126721 
nnet RMSE 469 : 0.1433333 


s: 470 
logit 470 : -0.494269 
logit mean 470 : -0.4407367 
logit RMSE 470 : 0.07132778 

boosting 470 : -0.5436854 
boosting mean 470 : -0.4949268 
boosting RMSE 470 : 0.1483798 

forest 470 : -0.3367215 
forest mean 470 : -0.3842309 
forest RMSE 470 : 0.05494821 

nnet 470 : -0.4470577 
nnet mean 470 : -0.4127453 
nnet RMSE 470 : 0.1431972 


s: 471 
logit 471 : -0.4042504 
logit mean 471 : -0.4406592 
logit RMSE 471 : 0.0712523 

boosting 471 : -0.3935609 
boosting mean 471 : -0.4947116 
boosting RMSE 471 : 0.1482225 

forest 471 : -0.3918902 
forest mean 471 : -0.3842472 
forest RMSE 471 : 0.05489112 

nnet 471 : -0.3929057 
nnet mean 471 : -0.4127032 
nnet RMSE 471 : 0.1430455 


s: 472 
logit 472 : -0.4958149 
logit mean 472 : -0.4407761 
logit RMSE 472 : 0.07131328 

boosting 472 : -0.5203539 
boosting mean 472 : -0.4947659 
boosting RMSE 472 : 0.1481690 

forest 472 : -0.4365138 
forest mean 472 : -0.3843579 
forest RMSE 472 : 0.0548587 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 472 : -0.1595136 
nnet mean 472 : -0.4121668 
nnet RMSE 472 : 0.1433220 


s: 473 
logit 473 : -0.4359325 
logit mean 473 : -0.4407658 
logit RMSE 473 : 0.07125701 

boosting 473 : -0.5142201 
boosting mean 473 : -0.4948071 
boosting RMSE 473 : 0.1481055 

forest 473 : -0.3230609 
forest mean 473 : -0.3842283 
forest RMSE 473 : 0.05491474 

nnet 473 : -0.2014517 
nnet mean 473 : -0.4117213 
nnet RMSE 473 : 0.1434611 


s: 474 
logit 474 : -0.3953128 
logit mean 474 : -0.4406699 
logit RMSE 474 : 0.07118213 

boosting 474 : -0.4889453 
boosting mean 474 : -0.4947947 
boosting RMSE 474 : 0.1480056 

forest 474 : -0.3672872 
forest mean 474 : -0.3841926 
forest RMSE 474 : 0.05487736 

nnet 474 : -0.4410036 
nnet mean 474 : -0.4117831 
nnet RMSE 474 : 0.1433221 


s: 475 
logit 475 : -0.4513896 
logit mean 475 : -0.4406925 
logit RMSE 475 : 0.07114625 

boosting 475 : -0.8102935 
boosting mean 475 : -0.4954589 
boosting RMSE 475 : 0.1490434 

forest 475 : -0.4452957 
forest mean 475 : -0.3843212 
forest RMSE 475 : 0.05485895 

nnet 475 : -0.4007321 
nnet mean 475 : -0.4117598 
nnet RMSE 475 : 0.1431712 


s: 476 
logit 476 : -0.4970004 
logit mean 476 : -0.4408108 
logit RMSE 476 : 0.0712104 

boosting 476 : -0.4196463 
boosting mean 476 : -0.4952996 
boosting RMSE 476 : 0.1488895 

forest 476 : -0.3609074 
forest mean 476 : -0.3842720 
forest RMSE 476 : 0.05483058 

nnet 476 : -0.4334257 
nnet mean 476 : -0.4118053 
nnet RMSE 476 : 0.1430289 


s: 477 
logit 477 : -0.4297105 
logit mean 477 : -0.4407875 
logit RMSE 477 : 0.07114872 

boosting 477 : -0.3842898 
boosting mean 477 : -0.4950669 
boosting RMSE 477 : 0.1487351 

forest 477 : -0.2885948 
forest mean 477 : -0.3840715 
forest RMSE 477 : 0.05501008 

nnet 477 : -0.1768462 
nnet mean 477 : -0.4113127 
nnet RMSE 477 : 0.1432438 


s: 478 
logit 478 : -0.3443004 
logit mean 478 : -0.4405857 
logit RMSE 478 : 0.0711199 

boosting 478 : -0.5890029 
boosting mean 478 : -0.4952634 
boosting RMSE 478 : 0.1488307 

forest 478 : -0.3954421 
forest mean 478 : -0.3840952 
forest RMSE 478 : 0.0549529 

nnet 478 : -0.2443741 
nnet mean 478 : -0.4109635 
nnet RMSE 478 : 0.1432708 


s: 479 
logit 479 : -0.4525865 
logit mean 479 : -0.4406107 
logit RMSE 479 : 0.07108625 

boosting 479 : -0.717188 
boosting mean 479 : -0.4957267 
boosting RMSE 479 : 0.1493799 

forest 479 : -0.4583941 
forest mean 479 : -0.3842504 
forest RMSE 479 : 0.05496031 

nnet 479 : -0.2708701 
nnet mean 479 : -0.410671 
nnet RMSE 479 : 0.1432427 


s: 480 
logit 480 : -0.3936601 
logit mean 480 : -0.4405129 
logit RMSE 480 : 0.07101275 

boosting 480 : -0.3987554 
boosting mean 480 : -0.4955247 
boosting RMSE 480 : 0.1492243 

forest 480 : -0.3362673 
forest mean 480 : -0.3841504 
forest RMSE 480 : 0.05498004 

nnet 480 : -0.2540191 
nnet mean 480 : -0.4103447 
nnet RMSE 480 : 0.1432485 


s: 481 
logit 481 : -0.3118145 
logit mean 481 : -0.4402453 
logit RMSE 481 : 0.07105276 

boosting 481 : -0.3160900 
boosting mean 481 : -0.4951517 
boosting RMSE 481 : 0.1491181 

forest 481 : -0.3954122 
forest mean 481 : -0.3841738 
forest RMSE 481 : 0.05492326 

nnet 481 : -0.3577834 
nnet mean 481 : -0.4102354 
nnet RMSE 481 : 0.1431124 


s: 482 
logit 482 : -0.4465417 
logit mean 482 : -0.4402584 
logit RMSE 482 : 0.07101066 

boosting 482 : -0.3372415 
boosting mean 482 : -0.494824 
boosting RMSE 482 : 0.1489908 

forest 482 : -0.3346965 
forest mean 482 : -0.3840712 
forest RMSE 482 : 0.05494682 

nnet 482 : -0.493276 
nnet mean 482 : -0.4104077 
nnet RMSE 482 : 0.1430270 


s: 483 
logit 483 : -0.4492849 
logit mean 483 : -0.4402771 
logit RMSE 483 : 0.07097255 

boosting 483 : -0.6610492 
boosting mean 483 : -0.4951682 
boosting RMSE 483 : 0.1493097 

forest 483 : -0.5012113 
forest mean 483 : -0.3843137 
forest RMSE 483 : 0.05508276 

nnet 483 : -0.7093336 
nnet mean 483 : -0.4110266 
nnet RMSE 483 : 0.1435705 


s: 484 
logit 484 : -0.4858087 
logit mean 484 : -0.4403712 
logit RMSE 484 : 0.0710064 

boosting 484 : -0.7451141 
boosting mean 484 : -0.4956846 
boosting RMSE 484 : 0.1499780 

forest 484 : -0.4123435 
forest mean 484 : -0.3843716 
forest RMSE 484 : 0.05502869 

nnet 484 : -0.438528 
nnet mean 484 : -0.4110834 
nnet RMSE 484 : 0.1434328 


s: 485 
logit 485 : -0.4582219 
logit mean 485 : -0.440408 
logit RMSE 485 : 0.07098241 

boosting 485 : -0.6914075 
boosting mean 485 : -0.4960882 
boosting RMSE 485 : 0.1504065 

forest 485 : -0.3392133 
forest mean 485 : -0.3842785 
forest RMSE 485 : 0.05504118 

nnet 485 : -0.3710565 
nnet mean 485 : -0.4110009 
nnet RMSE 485 : 0.1432909 


s: 486 
logit 486 : -0.4007052 
logit mean 486 : -0.4403263 
logit RMSE 486 : 0.07090935 

boosting 486 : -0.5108798 
boosting mean 486 : -0.4961186 
boosting RMSE 486 : 0.1503359 

forest 486 : -0.3963308 
forest mean 486 : -0.3843033 
forest RMSE 486 : 0.05498478 

nnet 486 : -0.4245699 
nnet mean 486 : -0.4110288 
nnet RMSE 486 : 0.1431477 


s: 487 
logit 487 : -0.4067319 
logit mean 487 : -0.4402573 
logit RMSE 487 : 0.07083717 

boosting 487 : -0.3981664 
boosting mean 487 : -0.4959175 
boosting RMSE 487 : 0.1501815 

forest 487 : -0.3635584 
forest mean 487 : -0.3842607 
forest RMSE 487 : 0.05495311 

nnet 487 : -0.1474289 
nnet mean 487 : -0.4104875 
nnet RMSE 487 : 0.1434580 


s: 488 
logit 488 : -0.4419508 
logit mean 488 : -0.4402608 
logit RMSE 488 : 0.07079003 

boosting 488 : -0.6921794 
boosting mean 488 : -0.4963196 
boosting RMSE 488 : 0.1506094 

forest 488 : -0.4455155 
forest mean 488 : -0.3843862 
forest RMSE 488 : 0.05493543 

nnet 488 : -0.3008519 
nnet mean 488 : -0.4102628 
nnet RMSE 488 : 0.1433812 


s: 489 
logit 489 : -0.3740718 
logit mean 489 : -0.4401254 
logit RMSE 489 : 0.07072733 

boosting 489 : -0.4179165 
boosting mean 489 : -0.4961593 
boosting RMSE 489 : 0.1504575 

forest 489 : -0.3791571 
forest mean 489 : -0.3843755 
forest RMSE 489 : 0.05488733 

nnet 489 : -0.4674331 
nnet mean 489 : -0.4103797 
nnet RMSE 489 : 0.1432669 


s: 490 
logit 490 : -0.4092186 
logit mean 490 : -0.4400623 
logit RMSE 490 : 0.07065635 

boosting 490 : -0.4762241 
boosting mean 490 : -0.4961186 
boosting RMSE 490 : 0.1503433 

forest 490 : -0.3524568 
forest mean 490 : -0.3843104 
forest RMSE 490 : 0.05487334 

nnet 490 : -0.4090973 
nnet mean 490 : -0.4103771 
nnet RMSE 490 : 0.1431213 


s: 491 
logit 491 : -0.4259421 
logit mean 491 : -0.4400336 
logit RMSE 491 : 0.07059407 

boosting 491 : -0.4900243 
boosting mean 491 : -0.4961062 
boosting RMSE 491 : 0.1502451 

forest 491 : -0.3742747 
forest mean 491 : -0.3842899 
forest RMSE 491 : 0.05482972 

nnet 491 : -0.4862229 
nnet mean 491 : -0.4105316 
nnet RMSE 491 : 0.1430284 


s: 492 
logit 492 : -0.4191038 
logit mean 492 : -0.439991 
logit RMSE 492 : 0.07052755 

boosting 492 : -0.441668 
boosting mean 492 : -0.4959956 
boosting RMSE 492 : 0.1501041 

forest 492 : -0.2259478 
forest mean 492 : -0.3839681 
forest RMSE 492 : 0.05533319 

nnet 492 : -0.3938496 
nnet mean 492 : -0.4104977 
nnet RMSE 492 : 0.1428832 


s: 493 
logit 493 : -0.4382634 
logit mean 493 : -0.4399875 
logit RMSE 493 : 0.07047706 

boosting 493 : -0.296807 
boosting mean 493 : -0.4955915 
boosting RMSE 493 : 0.1500238 

forest 493 : -0.3390099 
forest mean 493 : -0.3838769 
forest RMSE 493 : 0.05534525 

nnet 493 : -0.5175505 
nnet mean 493 : -0.4107148 
nnet RMSE 493 : 0.1428364 


s: 494 
logit 494 : -0.4698606 
logit mean 494 : -0.440048 
logit RMSE 494 : 0.07047582 

boosting 494 : -0.4826228 
boosting mean 494 : -0.4955653 
boosting RMSE 494 : 0.1499179 

forest 494 : -0.4045558 
forest mean 494 : -0.3839188 
forest RMSE 494 : 0.05528958 

nnet 494 : -0.4725971 
nnet mean 494 : -0.4108401 
nnet RMSE 494 : 0.1427291 


s: 495 
logit 495 : -0.389512 
logit mean 495 : -0.4399459 
logit RMSE 495 : 0.07040617 

boosting 495 : -0.5840684 
boosting mean 495 : -0.4957441 
boosting RMSE 495 : 0.1499948 

forest 495 : -0.3774607 
forest mean 495 : -0.3839057 
forest RMSE 495 : 0.055243 

nnet 495 : -0.532405 
nnet mean 495 : -0.4110857 
nnet RMSE 495 : 0.142709 


s: 496 
logit 496 : -0.4033817 
logit mean 496 : -0.4398722 
logit RMSE 496 : 0.07033533 

boosting 496 : -0.3817701 
boosting mean 496 : -0.4955143 
boosting RMSE 496 : 0.1498457 

forest 496 : -0.4302898 
forest mean 496 : -0.3839992 
forest RMSE 496 : 0.05520404 

nnet 496 : -0.3350006 
nnet mean 496 : -0.4109323 
nnet RMSE 496 : 0.1425950 


s: 497 
logit 497 : -0.4105171 
logit mean 497 : -0.4398131 
logit RMSE 497 : 0.07026611 

boosting 497 : -0.4377067 
boosting mean 497 : -0.495398 
boosting RMSE 497 : 0.1497045 

forest 497 : -0.4375791 
forest mean 497 : -0.3841070 
forest RMSE 497 : 0.05517423 

nnet 497 : -0.1043430 
nnet mean 497 : -0.4103154 
nnet RMSE 497 : 0.1430674 


s: 498 
logit 498 : -0.4200633 
logit mean 498 : -0.4397735 
logit RMSE 498 : 0.07020129 

boosting 498 : -0.4812158 
boosting mean 498 : -0.4953695 
boosting RMSE 498 : 0.1495984 

forest 498 : -0.3417116 
forest mean 498 : -0.3840219 
forest RMSE 498 : 0.05518066 

nnet 498 : -0.4093337 
nnet mean 498 : -0.4103134 
nnet RMSE 498 : 0.1429243 


s: 499 
logit 499 : -0.4488231 
logit mean 499 : -0.4397916 
logit RMSE 499 : 0.07016496 

boosting 499 : -0.5769086 
boosting mean 499 : -0.4955329 
boosting RMSE 499 : 0.1496581 

forest 499 : -0.4596961 
forest mean 499 : -0.3841736 
forest RMSE 499 : 0.05519007 

nnet 499 : -0.5340709 
nnet mean 499 : -0.4105615 
nnet RMSE 499 : 0.1429071 


s: 500 
logit 500 : -0.4594236 
logit mean 500 : -0.4398309 
logit RMSE 500 : 0.07014512 

boosting 500 : -0.5015605 
boosting mean 500 : -0.495545 
boosting RMSE 500 : 0.1495773 

forest 500 : -0.4161379 
forest mean 500 : -0.3842375 
forest RMSE 500 : 0.05513958 

nnet 500 : -0.5768394 
nnet mean 500 : -0.410894 
nnet RMSE 500 : 0.1429830 


s: 501 
logit 501 : -0.3859191 
logit mean 501 : -0.4397233 
logit RMSE 501 : 0.0700779 

boosting 501 : -0.5022275 
boosting mean 501 : -0.4955583 
boosting RMSE 501 : 0.1494977 

forest 501 : -0.3802729 
forest mean 501 : -0.3842296 
forest RMSE 501 : 0.05509157 

nnet 501 : -0.4637888 
nnet mean 501 : -0.4109996 
nnet RMSE 501 : 0.1428687 


s: 502 
logit 502 : -0.5175268 
logit mean 502 : -0.4398782 
logit RMSE 502 : 0.0702043 

boosting 502 : -0.3951227 
boosting mean 502 : -0.4953582 
boosting RMSE 502 : 0.1493489 

forest 502 : -0.5153894 
forest mean 502 : -0.3844909 
forest RMSE 502 : 0.05527711 

nnet 502 : -0.7380751 
nnet mean 502 : -0.4116511 
nnet RMSE 502 : 0.1435217 


s: 503 
logit 503 : -0.4593602 
logit mean 503 : -0.439917 
logit RMSE 503 : 0.07018441 

boosting 503 : -0.5159781 
boosting mean 503 : -0.4953992 
boosting RMSE 503 : 0.1492900 

forest 503 : -0.4192008 
forest mean 503 : -0.3845599 
forest RMSE 503 : 0.05522877 

nnet 503 : -0.5980888 
nnet mean 503 : -0.4120218 
nnet RMSE 503 : 0.1436508 


s: 504 
logit 504 : -0.3634352 
logit mean 504 : -0.4397652 
logit RMSE 504 : 0.07013366 

boosting 504 : -0.6813969 
boosting mean 504 : -0.4957683 
boosting RMSE 504 : 0.1496676 

forest 504 : -0.3695865 
forest mean 504 : -0.3845302 
forest RMSE 504 : 0.05519058 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 504 : -0.1306119 
nnet mean 504 : -0.4114634 
nnet RMSE 504 : 0.1440090 


s: 505 
logit 505 : -0.5083619 
logit mean 505 : -0.4399011 
logit RMSE 505 : 0.07022993 

boosting 505 : -0.3861324 
boosting mean 505 : -0.4955512 
boosting RMSE 505 : 0.1495206 

forest 505 : -0.4164284 
forest mean 505 : -0.3845933 
forest RMSE 505 : 0.05514076 

nnet 505 : -0.3816736 
nnet mean 505 : -0.4114044 
nnet RMSE 505 : 0.1438686 


s: 506 
logit 506 : -0.4600115 
logit mean 506 : -0.4399408 
logit RMSE 506 : 0.0702112 

boosting 506 : -0.4554611 
boosting mean 506 : -0.4954719 
boosting RMSE 506 : 0.1493931 

forest 506 : -0.4250553 
forest mean 506 : -0.3846733 
forest RMSE 506 : 0.0550975 

nnet 506 : -0.1351656 
nnet mean 506 : -0.4108585 
nnet RMSE 506 : 0.1442078 


s: 507 
logit 507 : -0.458935 
logit mean 507 : -0.4399783 
logit RMSE 507 : 0.07019074 

boosting 507 : -0.5609895 
boosting mean 507 : -0.4956012 
boosting RMSE 507 : 0.1494169 

forest 507 : -0.4032587 
forest mean 507 : -0.3847099 
forest RMSE 507 : 0.05504333 

nnet 507 : -0.5756371 
nnet mean 507 : -0.4111835 
nnet RMSE 507 : 0.1442765 


s: 508 
logit 508 : -0.3932778 
logit mean 508 : -0.4398863 
logit RMSE 508 : 0.07012226 

boosting 508 : -0.4504297 
boosting mean 508 : -0.4955122 
boosting RMSE 508 : 0.1492865 

forest 508 : -0.4225775 
forest mean 508 : -0.3847845 
forest RMSE 508 : 0.05499825 

nnet 508 : -0.3247265 
nnet mean 508 : -0.4110133 
nnet RMSE 508 : 0.1441731 


s: 509 
logit 509 : -0.4145706 
logit mean 509 : -0.4398366 
logit RMSE 509 : 0.07005632 

boosting 509 : -0.3231424 
boosting mean 509 : -0.4951736 
boosting RMSE 509 : 0.1491787 

forest 509 : -0.4267914 
forest mean 509 : -0.384867 
forest RMSE 509 : 0.05495703 

nnet 509 : -0.5187149 
nnet mean 509 : -0.4112249 
nnet RMSE 509 : 0.1441275 


s: 510 
logit 510 : -0.5322587 
logit mean 510 : -0.4400178 
logit RMSE 510 : 0.07023221 

boosting 510 : -0.3376743 
boosting mean 510 : -0.4948648 
boosting RMSE 510 : 0.1490579 

forest 510 : -0.3816659 
forest mean 510 : -0.3848607 
forest RMSE 510 : 0.05490912 

nnet 510 : -0.4116131 
nnet mean 510 : -0.4112257 
nnet RMSE 510 : 0.1439871 


s: 511 
logit 511 : -0.3521501 
logit mean 511 : -0.4398459 
logit RMSE 511 : 0.07019538 

boosting 511 : -0.5960727 
boosting mean 511 : -0.4950628 
boosting RMSE 511 : 0.1491644 

forest 511 : -0.4117844 
forest mean 511 : -0.3849134 
forest RMSE 511 : 0.05485785 

nnet 511 : -0.1805566 
nnet mean 511 : -0.4107743 
nnet RMSE 511 : 0.1441733 


s: 512 
logit 512 : -0.3935357 
logit mean 512 : -0.4397554 
logit RMSE 512 : 0.07012737 

boosting 512 : -0.5660556 
boosting mean 512 : -0.4952015 
boosting RMSE 512 : 0.1491993 

forest 512 : -0.4259640 
forest mean 512 : -0.3849936 
forest RMSE 512 : 0.05481626 

nnet 512 : -0.3549715 
nnet mean 512 : -0.4106653 
nnet RMSE 512 : 0.1440462 


s: 513 
logit 513 : -0.3774558 
logit mean 513 : -0.439634 
logit RMSE 513 : 0.07006606 

boosting 513 : -0.4690063 
boosting mean 513 : -0.4951504 
boosting RMSE 513 : 0.1490849 

forest 513 : -0.3559547 
forest mean 513 : -0.384937 
forest RMSE 513 : 0.05479732 

nnet 513 : -0.401835 
nnet mean 513 : -0.4106481 
nnet RMSE 513 : 0.1439058 


s: 514 
logit 514 : -0.5109373 
logit mean 514 : -0.4397727 
logit RMSE 514 : 0.0701687 

boosting 514 : -0.6546781 
boosting mean 514 : -0.4954608 
boosting RMSE 514 : 0.1493628 

forest 514 : -0.3590963 
forest mean 514 : -0.3848867 
forest RMSE 514 : 0.05477372 

nnet 514 : -0.3275813 
nnet mean 514 : -0.4104865 
nnet RMSE 514 : 0.1438012 


s: 515 
logit 515 : -0.3505445 
logit mean 515 : -0.4395994 
logit RMSE 515 : 0.0701344 

boosting 515 : -0.3443636 
boosting mean 515 : -0.4951674 
boosting RMSE 515 : 0.1492379 

forest 515 : -0.3432310 
forest mean 515 : -0.3848058 
forest RMSE 515 : 0.05477766 

nnet 515 : -0.4960678 
nnet mean 515 : -0.4106526 
nnet RMSE 515 : 0.1437239 


s: 516 
logit 516 : -0.4125934 
logit mean 516 : -0.4395471 
logit RMSE 516 : 0.0700686 

boosting 516 : -0.4531031 
boosting mean 516 : -0.4950859 
boosting RMSE 516 : 0.1491115 

forest 516 : -0.4471392 
forest mean 516 : -0.3849266 
forest RMSE 516 : 0.05476389 

nnet 516 : -0.4274293 
nnet mean 516 : -0.4106852 
nnet RMSE 516 : 0.1435896 


s: 517 
logit 517 : -0.3989954 
logit mean 517 : -0.4394687 
logit RMSE 517 : 0.07000082 

boosting 517 : -0.4053479 
boosting mean 517 : -0.4949123 
boosting RMSE 517 : 0.1489674 

forest 517 : -0.4349688 
forest mean 517 : -0.3850234 
forest RMSE 517 : 0.05473251 

nnet 517 : -0.4110066 
nnet mean 517 : -0.4106858 
nnet RMSE 517 : 0.1434515 


s: 518 
logit 518 : -0.5013996 
logit mean 518 : -0.4395882 
logit RMSE 518 : 0.07007499 

boosting 518 : -0.5581334 
boosting mean 518 : -0.4950343 
boosting RMSE 518 : 0.1489857 

forest 518 : -0.4072632 
forest mean 518 : -0.3850664 
forest RMSE 518 : 0.05468058 

nnet 518 : -0.6824389 
nnet mean 518 : -0.4112104 
nnet RMSE 518 : 0.1438492 


s: 519 
logit 519 : -0.3852709 
logit mean 519 : -0.4394836 
logit RMSE 519 : 0.07001043 

boosting 519 : -0.384165 
boosting mean 519 : -0.4948207 
boosting RMSE 519 : 0.1488437 

forest 519 : -0.4128903 
forest mean 519 : -0.38512 
forest RMSE 519 : 0.05463081 

nnet 519 : -0.3257664 
nnet mean 519 : -0.4110458 
nnet RMSE 519 : 0.1437475 


s: 520 
logit 520 : -0.4452373 
logit mean 520 : -0.4394946 
logit RMSE 520 : 0.06997121 

boosting 520 : -0.593217 
boosting mean 520 : -0.49501 
boosting RMSE 520 : 0.1489417 

forest 520 : -0.3696246 
forest mean 520 : -0.3850902 
forest RMSE 520 : 0.05459451 

nnet 520 : -0.3707064 
nnet mean 520 : -0.4109682 
nnet RMSE 520 : 0.1436150 


s: 521 
logit 521 : -0.3908397 
logit mean 521 : -0.4394013 
logit RMSE 521 : 0.06990518 

boosting 521 : -0.5279018 
boosting mean 521 : -0.4950731 
boosting RMSE 521 : 0.1489042 

forest 521 : -0.4001361 
forest mean 521 : -0.3851191 
forest RMSE 521 : 0.05454209 

nnet 521 : -0.5596994 
nnet mean 521 : -0.4112537 
nnet RMSE 521 : 0.1436476 


s: 522 
logit 522 : -0.4969718 
logit mean 522 : -0.4395115 
logit RMSE 522 : 0.06996704 

boosting 522 : -0.5833845 
boosting mean 522 : -0.4952423 
boosting RMSE 522 : 0.1489779 

forest 522 : -0.4612016 
forest mean 522 : -0.3852648 
forest RMSE 522 : 0.05455562 

nnet 522 : -0.3583375 
nnet mean 522 : -0.4111523 
nnet RMSE 522 : 0.1435215 


s: 523 
logit 523 : -0.3799871 
logit mean 523 : -0.4393977 
logit RMSE 523 : 0.0699056 

boosting 523 : -0.4837328 
boosting mean 523 : -0.4952203 
boosting RMSE 523 : 0.1488804 

forest 523 : -0.3236342 
forest mean 523 : -0.385147 
forest RMSE 523 : 0.05460564 

nnet 523 : -0.3958447 
nnet mean 523 : -0.411123 
nnet RMSE 523 : 0.1433843 


s: 524 
logit 524 : -0.4737522 
logit mean 524 : -0.4394633 
logit RMSE 524 : 0.06991314 

boosting 524 : -0.5408835 
boosting mean 524 : -0.4953074 
boosting RMSE 524 : 0.1488656 

forest 524 : -0.4428979 
forest mean 524 : -0.3852572 
forest RMSE 524 : 0.05458569 

nnet 524 : -0.450709 
nnet mean 524 : -0.4111986 
nnet RMSE 524 : 0.1432646 


s: 525 
logit 525 : -0.4507375 
logit mean 525 : -0.4394848 
logit RMSE 525 : 0.06988162 

boosting 525 : -0.5127849 
boosting mean 525 : -0.4953407 
boosting RMSE 525 : 0.1488051 

forest 525 : -0.4028517 
forest mean 525 : -0.3852907 
forest RMSE 525 : 0.05453382 

nnet 525 : -0.694066 
nnet mean 525 : -0.4117374 
nnet RMSE 525 : 0.1437023 


s: 526 
logit 526 : -0.4538155 
logit mean 526 : -0.439512 
logit RMSE 526 : 0.06985458 

boosting 526 : -0.5327578 
boosting mean 526 : -0.4954118 
boosting RMSE 526 : 0.1487763 

forest 526 : -0.3819106 
forest mean 526 : -0.3852843 
forest RMSE 526 : 0.05448767 

nnet 526 : -0.2472073 
nnet mean 526 : -0.4114246 
nnet RMSE 526 : 0.1437202 


s: 527 
logit 527 : -0.3852378 
logit mean 527 : -0.439409 
logit RMSE 527 : 0.06979123 

boosting 527 : -0.4258071 
boosting mean 527 : -0.4952797 
boosting RMSE 527 : 0.1486393 

forest 527 : -0.3834118 
forest mean 527 : -0.3852807 
forest RMSE 527 : 0.05444074 

nnet 527 : -0.4367353 
nnet mean 527 : -0.4114726 
nnet RMSE 527 : 0.1435927 


s: 528 
logit 528 : -0.4474369 
logit mean 528 : -0.4394242 
logit RMSE 528 : 0.06975567 

boosting 528 : -0.5170025 
boosting mean 528 : -0.4953209 
boosting RMSE 528 : 0.1485858 

forest 528 : -0.4150566 
forest mean 528 : -0.3853371 
forest RMSE 528 : 0.05439311 

nnet 528 : -0.3332427 
nnet mean 528 : -0.4113244 
nnet RMSE 528 : 0.1434860 


s: 529 
logit 529 : -0.4564399 
logit mean 529 : -0.4394564 
logit RMSE 529 : 0.0697329 

boosting 529 : -0.667158 
boosting mean 529 : -0.4956457 
boosting RMSE 529 : 0.148899 

forest 529 : -0.3024266 
forest mean 529 : -0.3851804 
forest RMSE 529 : 0.05450702 

nnet 529 : -0.3137824 
nnet mean 529 : -0.4111400 
nnet RMSE 529 : 0.1433994 


s: 530 
logit 530 : -0.3740697 
logit mean 530 : -0.439333 
logit RMSE 530 : 0.06967618 

boosting 530 : -0.5654751 
boosting mean 530 : -0.4957775 
boosting RMSE 530 : 0.1489320 

forest 530 : -0.4050876 
forest mean 530 : -0.3852179 
forest RMSE 530 : 0.05445602 

nnet 530 : -0.4503185 
nnet mean 530 : -0.411214 
nnet RMSE 530 : 0.1432807 


s: 531 
logit 531 : -0.4866946 
logit mean 531 : -0.4394222 
logit RMSE 531 : 0.06971214 

boosting 531 : -0.4953687 
boosting mean 531 : -0.4957767 
boosting RMSE 531 : 0.1488493 

forest 531 : -0.3951916 
forest mean 531 : -0.3852367 
forest RMSE 531 : 0.05440512 

nnet 531 : -0.4776512 
nnet mean 531 : -0.4113391 
nnet RMSE 531 : 0.1431854 


s: 532 
logit 532 : -0.4692629 
logit mean 532 : -0.4394783 
logit RMSE 532 : 0.0697113 

boosting 532 : -0.5552297 
boosting mean 532 : -0.4958885 
boosting RMSE 532 : 0.1488615 

forest 532 : -0.5181792 
forest mean 532 : -0.3854866 
forest RMSE 532 : 0.05459492 

nnet 532 : -0.6670393 
nnet mean 532 : -0.4118197 
nnet RMSE 532 : 0.1435185 


s: 533 
logit 533 : -0.4415202 
logit mean 533 : -0.4394821 
logit RMSE 533 : 0.06966909 

boosting 533 : -0.4836733 
boosting mean 533 : -0.4958655 
boosting RMSE 533 : 0.1487660 

forest 533 : -0.3260373 
forest mean 533 : -0.3853751 
forest RMSE 533 : 0.05463769 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 533 : -0.1717882 
nnet mean 533 : -0.4113694 
nnet RMSE 533 : 0.1437241 


s: 534 
logit 534 : -0.3212477 
logit mean 534 : -0.4392607 
logit RMSE 534 : 0.0696872 

boosting 534 : -0.4992404 
boosting mean 534 : -0.4958719 
boosting RMSE 534 : 0.1486886 

forest 534 : -0.3208042 
forest mean 534 : -0.3852542 
forest RMSE 534 : 0.05469398 

nnet 534 : -0.4152365 
nnet mean 534 : -0.4113766 
nnet RMSE 534 : 0.1435910 


s: 535 
logit 535 : -0.4078592 
logit mean 535 : -0.439202 
logit RMSE 535 : 0.06962287 

boosting 535 : -0.3664941 
boosting mean 535 : -0.49563 
boosting RMSE 535 : 0.1485567 

forest 535 : -0.4395717 
forest mean 535 : -0.3853557 
forest RMSE 535 : 0.05466962 

nnet 535 : -0.3405424 
nnet mean 535 : -0.4112442 
nnet RMSE 535 : 0.1434797 


s: 536 
logit 536 : -0.4720292 
logit mean 536 : -0.4392633 
logit RMSE 536 : 0.06962744 

boosting 536 : -0.6102868 
boosting mean 536 : -0.4958439 
boosting RMSE 536 : 0.1486957 

forest 536 : -0.2865236 
forest mean 536 : -0.3851713 
forest RMSE 536 : 0.05483808 

nnet 536 : -0.4291126 
nnet mean 536 : -0.4112776 
nnet RMSE 536 : 0.1433514 


s: 537 
logit 537 : -0.4255921 
logit mean 537 : -0.4392378 
logit RMSE 537 : 0.06957135 

boosting 537 : -0.59444 
boosting mean 537 : -0.4960276 
boosting RMSE 537 : 0.1487940 

forest 537 : -0.3638654 
forest mean 537 : -0.3851316 
forest RMSE 537 : 0.05480919 

nnet 537 : -0.338629 
nnet mean 537 : -0.4111423 
nnet RMSE 537 : 0.1432423 


s: 538 
logit 538 : -0.4175804 
logit mean 538 : -0.4391976 
logit RMSE 538 : 0.06951079 

boosting 538 : -0.3583809 
boosting mean 538 : -0.4957717 
boosting RMSE 538 : 0.1486664 

forest 538 : -0.4258238 
forest mean 538 : -0.3852073 
forest RMSE 538 : 0.05476954 

nnet 538 : -0.2605603 
nnet mean 538 : -0.4108624 
nnet RMSE 538 : 0.1432353 


s: 539 
logit 539 : -0.5071121 
logit mean 539 : -0.4393236 
logit RMSE 539 : 0.06959936 

boosting 539 : -0.4264296 
boosting mean 539 : -0.4956431 
boosting RMSE 539 : 0.1485328 

forest 539 : -0.4127027 
forest mean 539 : -0.3852583 
forest RMSE 539 : 0.05472145 

nnet 539 : -0.6029802 
nnet mean 539 : -0.4112188 
nnet RMSE 539 : 0.1433692 


s: 540 
logit 540 : -0.4615868 
logit mean 540 : -0.4393648 
logit RMSE 540 : 0.06958538 

boosting 540 : -0.5082634 
boosting mean 540 : -0.4956664 
boosting RMSE 540 : 0.1484683 

forest 540 : -0.4948456 
forest mean 540 : -0.3854612 
forest RMSE 540 : 0.0548229 

nnet 540 : -0.2912476 
nnet mean 540 : -0.4109967 
nnet RMSE 540 : 0.1433129 


s: 541 
logit 541 : -0.4447330 
logit mean 541 : -0.4393747 
logit RMSE 541 : 0.06954763 

boosting 541 : -0.3874128 
boosting mean 541 : -0.4954663 
boosting RMSE 541 : 0.1483321 

forest 541 : -0.3546219 
forest mean 541 : -0.3854042 
forest RMSE 541 : 0.05480694 

nnet 541 : -0.2458317 
nnet mean 541 : -0.4106914 
nnet RMSE 541 : 0.1433337 


s: 542 
logit 542 : -0.3960036 
logit mean 542 : -0.4392947 
logit RMSE 542 : 0.06948366 

boosting 542 : -0.4098745 
boosting mean 542 : -0.4953084 
boosting RMSE 542 : 0.1481958 

forest 542 : -0.3912532 
forest mean 542 : -0.385415 
forest RMSE 542 : 0.05475765 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 542 : -0.2064404 
nnet mean 542 : -0.4103145 
nnet RMSE 542 : 0.1434425 


s: 543 
logit 543 : -0.4016522 
logit mean 543 : -0.4392254 
logit RMSE 543 : 0.06941968 

boosting 543 : -0.3864235 
boosting mean 543 : -0.4951079 
boosting RMSE 543 : 0.1480604 

forest 543 : -0.3546808 
forest mean 543 : -0.3853584 
forest RMSE 543 : 0.05474176 

nnet 543 : -0.5054915 
nnet mean 543 : -0.4104898 
nnet RMSE 543 : 0.1433819 


s: 544 
logit 544 : -0.3473317 
logit mean 544 : -0.4390564 
logit RMSE 544 : 0.0693926 

boosting 544 : -0.2536736 
boosting mean 544 : -0.4946641 
boosting RMSE 544 : 0.1480572 

forest 544 : -0.3179761 
forest mean 544 : -0.3852345 
forest RMSE 544 : 0.05480437 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 544 : -0.2032544 
nnet mean 544 : -0.4101088 
nnet RMSE 544 : 0.1434982 


s: 545 
logit 545 : -0.4736373 
logit mean 545 : -0.4391199 
logit RMSE 545 : 0.06940063 

boosting 545 : -0.5619926 
boosting mean 545 : -0.4947876 
boosting RMSE 545 : 0.1480840 

forest 545 : -0.2723456 
forest mean 545 : -0.3850274 
forest RMSE 545 : 0.05502643 

nnet 545 : -0.4084155 
nnet mean 545 : -0.4101057 
nnet RMSE 545 : 0.1433669 


s: 546 
logit 546 : -0.4226356 
logit mean 546 : -0.4390897 
logit RMSE 546 : 0.06934381 

boosting 546 : -0.4218442 
boosting mean 546 : -0.494654 
boosting RMSE 546 : 0.1479513 

forest 546 : -0.4187199 
forest mean 546 : -0.3850891 
forest RMSE 546 : 0.05498186 

nnet 546 : -0.4121052 
nnet mean 546 : -0.4101094 
nnet RMSE 546 : 0.1432365 


s: 547 
logit 547 : -0.3651936 
logit mean 547 : -0.4389546 
logit RMSE 547 : 0.06929638 

boosting 547 : -0.4058821 
boosting mean 547 : -0.4944917 
boosting RMSE 547 : 0.1478162 

forest 547 : -0.3745481 
forest mean 547 : -0.3850698 
forest RMSE 547 : 0.05494236 

nnet 547 : -0.4762566 
nnet mean 547 : -0.4102303 
nnet RMSE 547 : 0.1431427 


s: 548 
logit 548 : -0.4270312 
logit mean 548 : -0.4389329 
logit RMSE 548 : 0.06924275 

boosting 548 : -0.3744131 
boosting mean 548 : -0.4942726 
boosting RMSE 548 : 0.1476853 

forest 548 : -0.3947255 
forest mean 548 : -0.3850874 
forest RMSE 548 : 0.05489266 

nnet 548 : -0.4344458 
nnet mean 548 : -0.4102745 
nnet RMSE 548 : 0.1430196 


s: 549 
logit 549 : -0.3798853 
logit mean 549 : -0.4388253 
logit RMSE 549 : 0.06918499 

boosting 549 : -0.4156276 
boosting mean 549 : -0.4941294 
boosting RMSE 549 : 0.1475522 

forest 549 : -0.4639766 
forest mean 549 : -0.3852311 
forest RMSE 549 : 0.05491058 

nnet 549 : -0.7197496 
nnet mean 549 : -0.4108382 
nnet RMSE 549 : 0.1435394 


s: 550 
logit 550 : -0.3653083 
logit mean 550 : -0.4386916 
logit RMSE 550 : 0.06913789 

boosting 550 : -0.5984921 
boosting mean 550 : -0.4943191 
boosting RMSE 550 : 0.1476608 

forest 550 : -0.3754886 
forest mean 550 : -0.3852134 
forest RMSE 550 : 0.05487059 

nnet 550 : -0.1664702 
nnet mean 550 : -0.4103939 
nnet RMSE 550 : 0.1437542 


s: 551 
logit 551 : -0.4679116 
logit mean 551 : -0.4387447 
logit RMSE 551 : 0.06913568 

boosting 551 : -0.5054632 
boosting mean 551 : -0.4943393 
boosting RMSE 551 : 0.1475951 

forest 551 : -0.4113398 
forest mean 551 : -0.3852608 
forest RMSE 551 : 0.0548229 

nnet 551 : -0.2645606 
nnet mean 551 : -0.4101292 
nnet RMSE 551 : 0.1437395 


s: 552 
logit 552 : -0.4759023 
logit mean 552 : -0.438812 
logit RMSE 552 : 0.06914854 

boosting 552 : -0.4906164 
boosting mean 552 : -0.4943326 
boosting RMSE 552 : 0.1475118 

forest 552 : -0.3521731 
forest mean 552 : -0.3852009 
forest RMSE 552 : 0.05481104 

nnet 552 : -0.3474050 
nnet mean 552 : -0.4100156 
nnet RMSE 552 : 0.1436267 


s: 553 
logit 553 : -0.3739958 
logit mean 553 : -0.4386948 
logit RMSE 553 : 0.06909484 

boosting 553 : -0.5734395 
boosting mean 553 : -0.4944756 
boosting RMSE 553 : 0.1475628 

forest 553 : -0.462058 
forest mean 553 : -0.3853399 
forest RMSE 553 : 0.05482501 

nnet 553 : -0.334733 
nnet mean 553 : -0.4098795 
nnet RMSE 553 : 0.1435236 


s: 554 
logit 554 : -0.5119293 
logit mean 554 : -0.438827 
logit RMSE 554 : 0.06919605 

boosting 554 : -0.4534072 
boosting mean 554 : -0.4944015 
boosting RMSE 554 : 0.1474470 

forest 554 : -0.4044964 
forest mean 554 : -0.3853745 
forest RMSE 554 : 0.05477584 

nnet 554 : -0.3849503 
nnet mean 554 : -0.4098345 
nnet RMSE 554 : 0.1433955 


s: 555 
logit 555 : -0.3477277 
logit mean 555 : -0.4386628 
logit RMSE 555 : 0.06916928 

boosting 555 : -0.5035007 
boosting mean 555 : -0.4944179 
boosting RMSE 555 : 0.1473796 

forest 555 : -0.3840244 
forest mean 555 : -0.385372 
forest RMSE 555 : 0.05473067 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 555 : -0.1955356 
nnet mean 555 : -0.4094484 
nnet RMSE 555 : 0.1435289 


s: 556 
logit 556 : -0.3746632 
logit mean 556 : -0.4385477 
logit RMSE 556 : 0.0691154 

boosting 556 : -0.4172504 
boosting mean 556 : -0.4942791 
boosting RMSE 556 : 0.1472489 

forest 556 : -0.360658 
forest mean 556 : -0.3853276 
forest RMSE 556 : 0.05470688 

nnet 556 : -0.3250624 
nnet mean 556 : -0.4092966 
nnet RMSE 556 : 0.1434349 


s: 557 
logit 557 : -0.4680686 
logit mean 557 : -0.4386007 
logit RMSE 557 : 0.06911354 

boosting 557 : -0.5238299 
boosting mean 557 : -0.4943322 
boosting RMSE 557 : 0.1472102 

forest 557 : -0.2790373 
forest mean 557 : -0.3851368 
forest RMSE 557 : 0.05489753 

nnet 557 : -0.5478363 
nnet mean 557 : -0.4095453 
nnet RMSE 557 : 0.1434430 


s: 558 
logit 558 : -0.3450607 
logit mean 558 : -0.4384331 
logit RMSE 558 : 0.06909074 

boosting 558 : -0.2228408 
boosting mean 558 : -0.4938456 
boosting RMSE 558 : 0.1472693 

forest 558 : -0.3461771 
forest mean 558 : -0.3850669 
forest RMSE 558 : 0.05489562 

nnet 558 : -0.2760983 
nnet mean 558 : -0.4093062 
nnet RMSE 558 : 0.1434103 


s: 559 
logit 559 : -0.3722971 
logit mean 559 : -0.4383148 
logit RMSE 559 : 0.06903886 

boosting 559 : -0.5412534 
boosting mean 559 : -0.4939304 
boosting RMSE 559 : 0.1472587 

forest 559 : -0.4154881 
forest mean 559 : -0.3851214 
forest RMSE 559 : 0.05485041 

nnet 559 : -0.4354376 
nnet mean 559 : -0.4093529 
nnet RMSE 559 : 0.1432898 


s: 560 
logit 560 : -0.4485201 
logit mean 560 : -0.438333 
logit RMSE 560 : 0.06900765 

boosting 560 : -0.5864974 
boosting mean 560 : -0.4940957 
boosting RMSE 560 : 0.1473381 

forest 560 : -0.4296684 
forest mean 560 : -0.3852009 
forest RMSE 560 : 0.05481575 

nnet 560 : -0.2189670 
nnet mean 560 : -0.4090129 
nnet RMSE 560 : 0.1433661 


s: 561 
logit 561 : -0.4694329 
logit mean 561 : -0.4383884 
logit RMSE 561 : 0.06900841 

boosting 561 : -0.6481614 
boosting mean 561 : -0.4943704 
boosting RMSE 561 : 0.1475791 

forest 561 : -0.3058093 
forest mean 561 : -0.3850594 
forest RMSE 561 : 0.05491106 

nnet 561 : -0.4765026 
nnet mean 561 : -0.4091332 
nnet RMSE 561 : 0.1432747 


s: 562 
logit 562 : -0.4755809 
logit mean 562 : -0.4384546 
logit RMSE 562 : 0.06902066 

boosting 562 : -0.567971 
boosting mean 562 : -0.4945013 
boosting RMSE 562 : 0.1476179 

forest 562 : -0.4051543 
forest mean 562 : -0.3850951 
forest RMSE 562 : 0.05486262 

nnet 562 : -0.5441886 
nnet mean 562 : -0.4093735 
nnet RMSE 562 : 0.1432763 


s: 563 
logit 563 : -0.4972587 
logit mean 563 : -0.4385591 
logit RMSE 563 : 0.06908105 

boosting 563 : -0.4510874 
boosting mean 563 : -0.4944242 
boosting RMSE 563 : 0.1475025 

forest 563 : -0.3892966 
forest mean 563 : -0.3851026 
forest RMSE 563 : 0.05481573 

nnet 563 : -0.4904482 
nnet mean 563 : -0.4095175 
nnet RMSE 563 : 0.1431997 


s: 564 
logit 564 : -0.3804368 
logit mean 564 : -0.438456 
logit RMSE 564 : 0.0690247 

boosting 564 : -0.3487933 
boosting mean 564 : -0.494166 
boosting RMSE 564 : 0.1473874 

forest 564 : -0.4185644 
forest mean 564 : -0.3851619 
forest RMSE 564 : 0.05477269 

nnet 564 : -0.5309823 
nnet mean 564 : -0.4097329 
nnet RMSE 564 : 0.143179 


s: 565 
logit 565 : -0.462222 
logit mean 565 : -0.4384981 
logit RMSE 565 : 0.06901325 

boosting 565 : -0.3308779 
boosting mean 565 : -0.493877 
boosting RMSE 565 : 0.1472856 

forest 565 : -0.3894788 
forest mean 565 : -0.3851696 
forest RMSE 565 : 0.05472599 

nnet 565 : -0.5946134 
nnet mean 565 : -0.4100601 
nnet RMSE 565 : 0.1432864 


s: 566 
logit 566 : -0.5262161 
logit mean 566 : -0.438653 
logit RMSE 566 : 0.06915605 

boosting 566 : -0.3631506 
boosting mean 566 : -0.493646 
boosting RMSE 566 : 0.1471636 

forest 566 : -0.3884816 
forest mean 566 : -0.3851754 
forest RMSE 566 : 0.05467977 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 566 : -0.1956833 
nnet mean 566 : -0.4096814 
nnet RMSE 566 : 0.1434171 


s: 567 
logit 567 : -0.3502363 
logit mean 567 : -0.4384971 
logit RMSE 567 : 0.06912664 

boosting 567 : -0.5438529 
boosting mean 567 : -0.4937346 
boosting RMSE 567 : 0.1471579 

forest 567 : -0.3544860 
forest mean 567 : -0.3851213 
forest RMSE 567 : 0.05466496 

nnet 567 : -0.3427556 
nnet mean 567 : -0.4095633 
nnet RMSE 567 : 0.1433107 


s: 568 
logit 568 : -0.452774 
logit mean 568 : -0.4385222 
logit RMSE 568 : 0.06910125 

boosting 568 : -0.4606269 
boosting mean 568 : -0.4936763 
boosting RMSE 568 : 0.1470503 

forest 568 : -0.3103447 
forest mean 568 : -0.3849897 
forest RMSE 568 : 0.05474621 

nnet 568 : -0.4423363 
nnet mean 568 : -0.409621 
nnet RMSE 568 : 0.1431955 


s: 569 
logit 569 : -0.3638146 
logit mean 569 : -0.4383909 
logit RMSE 569 : 0.06905717 

boosting 569 : -0.6466042 
boosting mean 569 : -0.493945 
boosting RMSE 569 : 0.1472843 

forest 569 : -0.4039690 
forest mean 569 : -0.385023 
forest RMSE 569 : 0.05469834 

nnet 569 : -0.5479101 
nnet mean 569 : -0.4098641 
nnet RMSE 569 : 0.1432040 


s: 570 
logit 570 : -0.3774953 
logit mean 570 : -0.4382841 
logit RMSE 570 : 0.069003 

boosting 570 : -0.3844962 
boosting mean 570 : -0.493753 
boosting RMSE 570 : 0.1471564 

forest 570 : -0.4320363 
forest mean 570 : -0.3851055 
forest RMSE 570 : 0.05466681 

nnet 570 : -0.4618858 
nnet mean 570 : -0.4099553 
nnet RMSE 570 : 0.1431018 


s: 571 
logit 571 : -0.3785507 
logit mean 571 : -0.4381795 
logit RMSE 571 : 0.0689484 

boosting 571 : -0.4663341 
boosting mean 571 : -0.493705 
boosting RMSE 571 : 0.1470537 

forest 571 : -0.3119145 
forest mean 571 : -0.3849773 
forest RMSE 571 : 0.05474317 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 571 : -0.2263185 
nnet mean 571 : -0.4096337 
nnet RMSE 571 : 0.1431610 


s: 572 
logit 572 : -0.3968626 
logit mean 572 : -0.4381073 
logit RMSE 572 : 0.06888823 

boosting 572 : -0.1956934 
boosting mean 572 : -0.493184 
boosting RMSE 572 : 0.1471733 

forest 572 : -0.2282996 
forest mean 572 : -0.3847034 
forest RMSE 572 : 0.05516444 

nnet 572 : -0.501734 
nnet mean 572 : -0.4097948 
nnet RMSE 572 : 0.1430991 


s: 573 
logit 573 : -0.4142766 
logit mean 573 : -0.4380657 
logit RMSE 573 : 0.06883067 

boosting 573 : -0.605523 
boosting mean 573 : -0.4933801 
boosting RMSE 573 : 0.1472952 

forest 573 : -0.4044043 
forest mean 573 : -0.3847378 
forest RMSE 573 : 0.05511659 

nnet 573 : -0.607897 
nnet mean 573 : -0.4101405 
nnet RMSE 573 : 0.1432377 


s: 574 
logit 574 : -0.3593164 
logit mean 574 : -0.4379285 
logit RMSE 574 : 0.06879165 

boosting 574 : -0.4716576 
boosting mean 574 : -0.4933422 
boosting RMSE 574 : 0.1471973 

forest 574 : -0.3437635 
forest mean 574 : -0.3846664 
forest RMSE 574 : 0.05511856 

nnet 574 : -0.3724160 
nnet mean 574 : -0.4100748 
nnet RMSE 574 : 0.1431175 


s: 575 
logit 575 : -0.4021869 
logit mean 575 : -0.4378663 
logit RMSE 575 : 0.06873187 

boosting 575 : -0.5874757 
boosting mean 575 : -0.4935059 
boosting RMSE 575 : 0.1472769 

forest 575 : -0.5024522 
forest mean 575 : -0.3848712 
forest RMSE 575 : 0.0552361 

nnet 575 : -0.4154286 
nnet mean 575 : -0.4100841 
nnet RMSE 575 : 0.1429944 


s: 576 
logit 576 : -0.5507194 
logit mean 576 : -0.4380622 
logit RMSE 576 : 0.06895873 

boosting 576 : -0.5763986 
boosting mean 576 : -0.4936498 
boosting RMSE 576 : 0.1473324 

forest 576 : -0.4269896 
forest mean 576 : -0.3849444 
forest RMSE 576 : 0.05519959 

nnet 576 : -0.4617557 
nnet mean 576 : -0.4101738 
nnet RMSE 576 : 0.1428934 


s: 577 
logit 577 : -0.4897715 
logit mean 577 : -0.4381519 
logit RMSE 577 : 0.06900023 

boosting 577 : -0.5069445 
boosting mean 577 : -0.4936729 
boosting RMSE 577 : 0.147272 

forest 577 : -0.3922975 
forest mean 577 : -0.3849571 
forest RMSE 577 : 0.05515267 

nnet 577 : -0.5722905 
nnet mean 577 : -0.4104547 
nnet RMSE 577 : 0.1429496 


s: 578 
logit 578 : -0.4640669 
logit mean 578 : -0.4381967 
logit RMSE 578 : 0.068992 

boosting 578 : -0.3993764 
boosting mean 578 : -0.4935097 
boosting RMSE 578 : 0.1471446 

forest 578 : -0.3366122 
forest mean 578 : -0.3848735 
forest RMSE 578 : 0.05516798 

nnet 578 : -0.2890117 
nnet mean 578 : -0.4102446 
nnet RMSE 578 : 0.1429005 


s: 579 
logit 579 : -0.5177758 
logit mean 579 : -0.4383341 
logit RMSE 579 : 0.06910595 

boosting 579 : -0.3969745 
boosting mean 579 : -0.493343 
boosting RMSE 579 : 0.1470175 

forest 579 : -0.3879617 
forest mean 579 : -0.3848788 
forest RMSE 579 : 0.05512259 

nnet 579 : -0.4259386 
nnet mean 579 : -0.4102717 
nnet RMSE 579 : 0.1427811 


s: 580 
logit 580 : -0.4840489 
logit mean 580 : -0.438413 
logit RMSE 580 : 0.06913449 

boosting 580 : -0.5965925 
boosting mean 580 : -0.493521 
boosting RMSE 580 : 0.1471173 

forest 580 : -0.435257 
forest mean 580 : -0.3849657 
forest RMSE 580 : 0.0550945 

nnet 580 : -0.4624149 
nnet mean 580 : -0.4103616 
nnet RMSE 580 : 0.1426815 


s: 581 
logit 581 : -0.4140100 
logit mean 581 : -0.438371 
logit RMSE 581 : 0.06907741 

boosting 581 : -0.4117851 
boosting mean 581 : -0.4933803 
boosting RMSE 581 : 0.1469915 

forest 581 : -0.3779767 
forest mean 581 : -0.3849536 
forest RMSE 581 : 0.05505465 

nnet 581 : -0.3178122 
nnet mean 581 : -0.4102023 
nnet RMSE 581 : 0.1425994 


s: 582 
logit 582 : -0.4199589 
logit mean 582 : -0.4383393 
logit RMSE 582 : 0.069023 

boosting 582 : -0.6211936 
boosting mean 582 : -0.4936 
boosting RMSE 582 : 0.1471511 

forest 582 : -0.3754539 
forest mean 582 : -0.3849373 
forest RMSE 582 : 0.05501674 

nnet 582 : -0.2577579 
nnet mean 582 : -0.4099404 
nnet RMSE 582 : 0.1425988 


s: 583 
logit 583 : -0.4441182 
logit mean 583 : -0.4383492 
logit RMSE 583 : 0.06898798 

boosting 583 : -0.2557529 
boosting mean 583 : -0.493192 
boosting RMSE 583 : 0.1471461 

forest 583 : -0.3792743 
forest mean 583 : -0.3849276 
forest RMSE 583 : 0.05497624 

nnet 583 : -0.4713654 
nnet mean 583 : -0.4100458 
nnet RMSE 583 : 0.1425071 


s: 584 
logit 584 : -0.4382978 
logit mean 584 : -0.4383491 
logit RMSE 584 : 0.0689471 

boosting 584 : -0.4558486 
boosting mean 584 : -0.493128 
boosting RMSE 584 : 0.1470383 

forest 584 : -0.4291785 
forest mean 584 : -0.3850034 
forest RMSE 584 : 0.05494242 

nnet 584 : -0.4579062 
nnet mean 584 : -0.4101277 
nnet RMSE 584 : 0.1424052 


s: 585 
logit 585 : -0.426063 
logit mean 585 : -0.4383281 
logit RMSE 585 : 0.06889658 

boosting 585 : -0.4957224 
boosting mean 585 : -0.4931325 
boosting RMSE 585 : 0.1469658 

forest 585 : -0.3787318 
forest mean 585 : -0.3849926 
forest RMSE 585 : 0.05490248 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 585 : -0.2574364 
nnet mean 585 : -0.4098667 
nnet RMSE 585 : 0.1424055 


s: 586 
logit 586 : -0.5210911 
logit mean 586 : -0.4384694 
logit RMSE 586 : 0.06901928 

boosting 586 : -0.7088073 
boosting mean 586 : -0.4935005 
boosting RMSE 586 : 0.1473935 

forest 586 : -0.38226 
forest mean 586 : -0.384988 
forest RMSE 586 : 0.05486051 

nnet 586 : -0.2842964 
nnet mean 586 : -0.4096524 
nnet RMSE 586 : 0.1423642 


s: 587 
logit 587 : -0.363624 
logit mean 587 : -0.4383419 
logit RMSE 587 : 0.0689768 

boosting 587 : -0.4835872 
boosting mean 587 : -0.4934836 
boosting RMSE 587 : 0.1473083 

forest 587 : -0.3212824 
forest mean 587 : -0.3848795 
forest RMSE 587 : 0.05490997 

nnet 587 : -0.513868 
nnet mean 587 : -0.40983 
nnet RMSE 587 : 0.1423205 


s: 588 
logit 588 : -0.3429497 
logit mean 588 : -0.4381796 
logit RMSE 588 : 0.06895827 

boosting 588 : -0.3473111 
boosting mean 588 : -0.493235 
boosting RMSE 588 : 0.147199 

forest 588 : -0.3784485 
forest mean 588 : -0.3848685 
forest RMSE 588 : 0.05487045 

nnet 588 : -0.6146717 
nnet mean 588 : -0.4101783 
nnet RMSE 588 : 0.1424747 


s: 589 
logit 589 : -0.4031847 
logit mean 589 : -0.4381202 
logit RMSE 589 : 0.06889983 

boosting 589 : -0.5335844 
boosting mean 589 : -0.4933035 
boosting RMSE 589 : 0.1471769 

forest 589 : -0.4132501 
forest mean 589 : -0.3849167 
forest RMSE 589 : 0.05482657 

nnet 589 : -0.4471107 
nnet mean 589 : -0.4102410 
nnet RMSE 589 : 0.1423670 


s: 590 
logit 590 : -0.3863802 
logit mean 590 : -0.4380325 
logit RMSE 590 : 0.0688437 

boosting 590 : -0.6314915 
boosting mean 590 : -0.4935378 
boosting RMSE 590 : 0.1473607 

forest 590 : -0.3367588 
forest mean 590 : -0.3848351 
forest RMSE 590 : 0.05484193 

nnet 590 : -0.4450973 
nnet mean 590 : -0.4103001 
nnet RMSE 590 : 0.1422584 


s: 591 
logit 591 : -0.468847 
logit mean 591 : -0.4380847 
logit RMSE 591 : 0.06884371 

boosting 591 : -0.6507097 
boosting mean 591 : -0.4938037 
boosting RMSE 591 : 0.1475967 

forest 591 : -0.3522687 
forest mean 591 : -0.38478 
forest RMSE 591 : 0.05483067 

nnet 591 : -0.5591877 
nnet mean 591 : -0.4105520 
nnet RMSE 591 : 0.1422887 


s: 592 
logit 592 : -0.4831758 
logit mean 592 : -0.4381608 
logit RMSE 592 : 0.06887043 

boosting 592 : -0.5183952 
boosting mean 592 : -0.4938452 
boosting RMSE 592 : 0.1475522 

forest 592 : -0.4660769 
forest mean 592 : -0.3849173 
forest RMSE 592 : 0.05485162 

nnet 592 : -0.6296732 
nnet mean 592 : -0.4109222 
nnet RMSE 592 : 0.1424815 


s: 593 
logit 593 : -0.4400235 
logit mean 593 : -0.438164 
logit RMSE 593 : 0.06883197 

boosting 593 : -0.7586413 
boosting mean 593 : -0.4942918 
boosting RMSE 593 : 0.1481616 

forest 593 : -0.4110846 
forest mean 593 : -0.3849614 
forest RMSE 593 : 0.05480724 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 593 : -0.1834824 
nnet mean 593 : -0.4105386 
nnet RMSE 593 : 0.1426387 


s: 594 
logit 594 : -0.4076259 
logit mean 594 : -0.4381126 
logit RMSE 594 : 0.06877471 

boosting 594 : -0.3556497 
boosting mean 594 : -0.4940584 
boosting RMSE 594 : 0.1480480 

forest 594 : -0.3561072 
forest mean 594 : -0.3849129 
forest RMSE 594 : 0.05479069 

nnet 594 : -0.6202393 
nnet mean 594 : -0.4108917 
nnet RMSE 594 : 0.1428048 


s: 595 
logit 595 : -0.4188343 
logit mean 595 : -0.4380802 
logit RMSE 595 : 0.06872123 

boosting 595 : -0.8980914 
boosting mean 595 : -0.4947374 
boosting RMSE 595 : 0.1493263 

forest 595 : -0.3871634 
forest mean 595 : -0.3849166 
forest RMSE 595 : 0.05474716 

nnet 595 : -0.4112812 
nnet mean 595 : -0.4108923 
nnet RMSE 595 : 0.1426855 


s: 596 
logit 596 : -0.4931405 
logit mean 596 : -0.4381726 
logit RMSE 596 : 0.06876947 

boosting 596 : -0.7036143 
boosting mean 596 : -0.4950879 
boosting RMSE 596 : 0.1497184 

forest 596 : -0.3726986 
forest mean 596 : -0.3848961 
forest RMSE 596 : 0.05471264 

nnet 596 : -0.3263758 
nnet mean 596 : -0.4107505 
nnet RMSE 596 : 0.1425976 


s: 597 
logit 597 : -0.5264114 
logit mean 597 : -0.4383204 
logit RMSE 597 : 0.06890635 

boosting 597 : -0.5009022 
boosting mean 597 : -0.4950976 
boosting RMSE 597 : 0.1496499 

forest 597 : -0.4088186 
forest mean 597 : -0.3849362 
forest RMSE 597 : 0.05466799 

nnet 597 : -0.2489609 
nnet mean 597 : -0.4104795 
nnet RMSE 597 : 0.1426122 


s: 598 
logit 598 : -0.5225955 
logit mean 598 : -0.4384613 
logit RMSE 598 : 0.069031 

boosting 598 : -0.4413088 
boosting mean 598 : -0.4950077 
boosting RMSE 598 : 0.1495343 

forest 598 : -0.3884976 
forest mean 598 : -0.3849422 
forest RMSE 598 : 0.05462428 

nnet 598 : -0.3727686 
nnet mean 598 : -0.4104165 
nnet RMSE 598 : 0.1424973 


s: 599 
logit 599 : -0.4384470 
logit mean 599 : -0.4384613 
logit RMSE 599 : 0.06899123 

boosting 599 : -0.5433974 
boosting mean 599 : -0.4950885 
boosting RMSE 599 : 0.1495242 

forest 599 : -0.4138127 
forest mean 599 : -0.3849904 
forest RMSE 599 : 0.05458159 

nnet 599 : -0.3942162 
nnet mean 599 : -0.4103894 
nnet RMSE 599 : 0.1423785 


s: 600 
logit 600 : -0.4821537 
logit mean 600 : -0.4385341 
logit RMSE 600 : 0.06901526 

boosting 600 : -0.5917932 
boosting mean 600 : -0.4952496 
boosting RMSE 600 : 0.1496046 

forest 600 : -0.3698905 
forest mean 600 : -0.3849652 
forest RMSE 600 : 0.05454993 

nnet 600 : -0.4796477 
nnet mean 600 : -0.4105048 
nnet RMSE 600 : 0.1422969 


s: 601 
logit 601 : -0.4465184 
logit mean 601 : -0.4385474 
logit RMSE 601 : 0.06898392 

boosting 601 : -0.8059621 
boosting mean 601 : -0.4957666 
boosting RMSE 601 : 0.1503945 

forest 601 : -0.3771360 
forest mean 601 : -0.3849522 
forest RMSE 601 : 0.05451251 

nnet 601 : -0.4111007 
nnet mean 601 : -0.4105058 
nnet RMSE 601 : 0.1421792 


s: 602 
logit 602 : -0.4210913 
logit mean 602 : -0.4385184 
logit RMSE 602 : 0.06893196 

boosting 602 : -0.6314358 
boosting mean 602 : -0.495992 
boosting RMSE 602 : 0.1505653 

forest 602 : -0.424394 
forest mean 602 : -0.3850177 
forest RMSE 602 : 0.05447629 

nnet 602 : -0.5281043 
nnet mean 602 : -0.4107012 
nnet RMSE 602 : 0.142157 


s: 603 
logit 603 : -0.4622913 
logit mean 603 : -0.4385578 
logit RMSE 603 : 0.06892148 

boosting 603 : -0.3527331 
boosting mean 603 : -0.4957544 
boosting RMSE 603 : 0.1504527 

forest 603 : -0.3445375 
forest mean 603 : -0.3849506 
forest RMSE 603 : 0.05447794 

nnet 603 : -0.4090571 
nnet mean 603 : -0.4106985 
nnet RMSE 603 : 0.1420395 


s: 604 
logit 604 : -0.4534265 
logit mean 604 : -0.4385824 
logit RMSE 604 : 0.0688987 

boosting 604 : -0.6022626 
boosting mean 604 : -0.4959308 
boosting RMSE 604 : 0.1505533 

forest 604 : -0.3594696 
forest mean 604 : -0.3849084 
forest RMSE 604 : 0.0544578 

nnet 604 : -0.5414719 
nnet mean 604 : -0.410915 
nnet RMSE 604 : 0.1420386 


s: 605 
logit 605 : -0.5104866 
logit mean 605 : -0.4387013 
logit RMSE 605 : 0.06898813 

boosting 605 : -0.6814672 
boosting mean 605 : -0.4962374 
boosting RMSE 605 : 0.1508634 

forest 605 : -0.4358949 
forest mean 605 : -0.3849926 
forest RMSE 605 : 0.05443234 

nnet 605 : -0.5501705 
nnet mean 605 : -0.4111451 
nnet RMSE 605 : 0.1420524 


s: 606 
logit 606 : -0.4878397 
logit mean 606 : -0.4387823 
logit RMSE 606 : 0.06902348 

boosting 606 : -0.511989 
boosting mean 606 : -0.4962634 
boosting RMSE 606 : 0.1508075 

forest 606 : -0.3457373 
forest mean 606 : -0.3849279 
forest RMSE 606 : 0.05443206 

nnet 606 : -0.326882 
nnet mean 606 : -0.4110061 
nnet RMSE 606 : 0.1419663 


s: 607 
logit 607 : -0.3876443 
logit mean 607 : -0.4386981 
logit RMSE 607 : 0.06896843 

boosting 607 : -0.5114034 
boosting mean 607 : -0.4962884 
boosting RMSE 607 : 0.1507511 

forest 607 : -0.339302 
forest mean 607 : -0.3848527 
forest RMSE 607 : 0.05444298 

nnet 607 : -0.2931664 
nnet mean 607 : -0.4108120 
nnet RMSE 607 : 0.1419155 


s: 608 
logit 608 : -0.4589994 
logit mean 608 : -0.4387315 
logit RMSE 608 : 0.06895321 

boosting 608 : -0.5599264 
boosting mean 608 : -0.496393 
boosting RMSE 608 : 0.1507666 

forest 608 : -0.4784368 
forest mean 608 : -0.3850066 
forest RMSE 608 : 0.05449112 

nnet 608 : -0.1949088 
nnet mean 608 : -0.4104569 
nnet RMSE 608 : 0.1420425 


s: 609 
logit 609 : -0.443988 
logit mean 609 : -0.4387401 
logit RMSE 609 : 0.06891963 

boosting 609 : -0.5095616 
boosting mean 609 : -0.4964147 
boosting RMSE 609 : 0.1507082 

forest 609 : -0.2910038 
forest mean 609 : -0.3848523 
forest RMSE 609 : 0.05462521 

nnet 609 : -0.4569608 
nnet mean 609 : -0.4105332 
nnet RMSE 609 : 0.1419446 


s: 610 
logit 610 : -0.4106884 
logit mean 610 : -0.4386941 
logit RMSE 610 : 0.06886448 

boosting 610 : -0.4407814 
boosting mean 610 : -0.4963235 
boosting RMSE 610 : 0.1505937 

forest 610 : -0.420455 
forest mean 610 : -0.3849106 
forest RMSE 610 : 0.0545867 

nnet 610 : -0.2708739 
nnet mean 610 : -0.4103043 
nnet RMSE 610 : 0.1419245 


s: 611 
logit 611 : -0.3909718 
logit mean 611 : -0.438616 
logit RMSE 611 : 0.06880907 

boosting 611 : -0.5299597 
boosting mean 611 : -0.4963785 
boosting RMSE 611 : 0.1505622 

forest 611 : -0.4862421 
forest mean 611 : -0.3850765 
forest RMSE 611 : 0.05465349 

nnet 611 : -0.3806815 
nnet mean 611 : -0.4102558 
nnet RMSE 611 : 0.1418105 


s: 612 
logit 612 : -0.4266674 
logit mean 612 : -0.4385965 
logit RMSE 612 : 0.06876128 

boosting 612 : -0.5960147 
boosting mean 612 : -0.4965413 
boosting RMSE 612 : 0.1506477 

forest 612 : -0.5135911 
forest mean 612 : -0.3852865 
forest RMSE 612 : 0.05480152 

nnet 612 : -0.5847086 
nnet mean 612 : -0.4105408 
nnet RMSE 612 : 0.1418912 


s: 613 
logit 613 : -0.460045 
logit mean 613 : -0.4386315 
logit RMSE 613 : 0.06874796 

boosting 613 : -0.5631615 
boosting mean 613 : -0.49665 
boosting RMSE 613 : 0.1506689 

forest 613 : -0.279079 
forest mean 613 : -0.3851132 
forest RMSE 613 : 0.05497418 

nnet 613 : -0.4840274 
nnet mean 613 : -0.4106607 
nnet RMSE 613 : 0.141816 


s: 614 
logit 614 : -0.3505021 
logit mean 614 : -0.438488 
logit RMSE 614 : 0.068721 

boosting 614 : -0.4455865 
boosting mean 614 : -0.4965668 
boosting RMSE 614 : 0.1505574 

forest 614 : -0.4064204 
forest mean 614 : -0.3851479 
forest RMSE 614 : 0.05493001 

nnet 614 : -0.4119875 
nnet mean 614 : -0.4106629 
nnet RMSE 614 : 0.1417013 


s: 615 
logit 615 : -0.4548646 
logit mean 615 : -0.4385146 
logit RMSE 615 : 0.06870073 

boosting 615 : -0.4420976 
boosting mean 615 : -0.4964783 
boosting RMSE 615 : 0.1504445 

forest 615 : -0.3651459 
forest mean 615 : -0.3851154 
forest RMSE 615 : 0.05490332 

nnet 615 : -0.4697114 
nnet mean 615 : -0.4107589 
nnet RMSE 615 : 0.1416140 


s: 616 
logit 616 : -0.3785106 
logit mean 616 : -0.4384172 
logit RMSE 616 : 0.0686504 

boosting 616 : -0.5197802 
boosting mean 616 : -0.4965161 
boosting RMSE 616 : 0.1503998 

forest 616 : -0.4319178 
forest mean 616 : -0.3851914 
forest RMSE 616 : 0.05487381 

nnet 616 : -0.2464466 
nnet mean 616 : -0.4104922 
nnet RMSE 616 : 0.1416342 


s: 617 
logit 617 : -0.482635 
logit mean 617 : -0.4384888 
logit RMSE 617 : 0.06867538 

boosting 617 : -0.4270978 
boosting mean 617 : -0.4964036 
boosting RMSE 617 : 0.1502819 

forest 617 : -0.3979212 
forest mean 617 : -0.385212 
forest RMSE 617 : 0.05482939 

nnet 617 : -0.4460046 
nnet mean 617 : -0.4105497 
nnet RMSE 617 : 0.1415314 


s: 618 
logit 618 : -0.4262465 
logit mean 618 : -0.438469 
logit RMSE 618 : 0.06862791 

boosting 618 : -0.3792006 
boosting mean 618 : -0.4962139 
boosting RMSE 618 : 0.1501625 

forest 618 : -0.4289757 
forest mean 618 : -0.3852828 
forest RMSE 618 : 0.05479741 

nnet 618 : -0.3489416 
nnet mean 618 : -0.41045 
nnet RMSE 618 : 0.1414318 


s: 619 
logit 619 : -0.4103314 
logit mean 619 : -0.4384236 
logit RMSE 619 : 0.06857371 

boosting 619 : -0.5225116 
boosting mean 619 : -0.4962564 
boosting RMSE 619 : 0.150122 

forest 619 : -0.4011675 
forest mean 619 : -0.3853085 
forest RMSE 619 : 0.05475315 

nnet 619 : -0.2571281 
nnet mean 619 : -0.4102023 
nnet RMSE 619 : 0.1414341 


s: 620 
logit 620 : -0.4911203 
logit mean 620 : -0.4385086 
logit RMSE 620 : 0.06861604 

boosting 620 : -0.3432801 
boosting mean 620 : -0.4960097 
boosting RMSE 620 : 0.1500182 

forest 620 : -0.4030109 
forest mean 620 : -0.385337 
forest RMSE 620 : 0.05470911 

nnet 620 : -0.2221814 
nnet mean 620 : -0.4098991 
nnet RMSE 620 : 0.1415004 


s: 621 
logit 621 : -0.3958399 
logit mean 621 : -0.4384399 
logit RMSE 621 : 0.06856098 

boosting 621 : -0.4520639 
boosting mean 621 : -0.4959389 
boosting RMSE 621 : 0.1499119 

forest 621 : -0.4294841 
forest mean 621 : -0.3854081 
forest RMSE 621 : 0.05467784 

nnet 621 : -0.2181782 
nnet mean 621 : -0.4095903 
nnet RMSE 621 : 0.1415745 


s: 622 
logit 622 : -0.3693047 
logit mean 622 : -0.4383287 
logit RMSE 622 : 0.0685169 

boosting 622 : -0.3654676 
boosting mean 622 : -0.4957291 
boosting RMSE 622 : 0.1497977 

forest 622 : -0.3507079 
forest mean 622 : -0.3853523 
forest RMSE 622 : 0.05466961 

nnet 622 : -0.351065 
nnet mean 622 : -0.4094962 
nnet RMSE 622 : 0.1414743 


s: 623 
logit 623 : -0.3470765 
logit mean 623 : -0.4381822 
logit RMSE 623 : 0.06849471 

boosting 623 : -0.5363921 
boosting mean 623 : -0.4957944 
boosting RMSE 623 : 0.1497772 

forest 623 : -0.3904901 
forest mean 623 : -0.3853606 
forest RMSE 623 : 0.05462704 

nnet 623 : -0.5429223 
nnet mean 623 : -0.4097104 
nnet RMSE 623 : 0.1414766 


s: 624 
logit 624 : -0.3898048 
logit mean 624 : -0.4381047 
logit RMSE 624 : 0.06844102 

boosting 624 : -0.3201298 
boosting mean 624 : -0.4955129 
boosting RMSE 624 : 0.1496913 

forest 624 : -0.3520650 
forest mean 624 : -0.3853072 
forest RMSE 624 : 0.05461698 

nnet 624 : -0.2900093 
nnet mean 624 : -0.4095186 
nnet RMSE 624 : 0.1414318 


s: 625 
logit 625 : -0.4073986 
logit mean 625 : -0.4380556 
logit RMSE 625 : 0.06838689 

boosting 625 : -0.4480759 
boosting mean 625 : -0.495437 
boosting RMSE 625 : 0.1495838 

forest 625 : -0.4584849 
forest mean 625 : -0.3854243 
forest RMSE 625 : 0.05462338 

nnet 625 : -0.2400908 
nnet mean 625 : -0.4092475 
nnet RMSE 625 : 0.1414633 


s: 626 
logit 626 : -0.4119692 
logit mean 626 : -0.4380139 
logit RMSE 626 : 0.06833392 

boosting 626 : -0.5103652 
boosting mean 626 : -0.4954608 
boosting RMSE 626 : 0.1495294 

forest 626 : -0.3966079 
forest mean 626 : -0.3854422 
forest RMSE 626 : 0.05457991 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 626 : -0.20251 
nnet mean 626 : -0.4089172 
nnet RMSE 626 : 0.1415704 


s: 627 
logit 627 : -0.3953322 
logit mean 627 : -0.4379458 
logit RMSE 627 : 0.06827966 

boosting 627 : -0.5500443 
boosting mean 627 : -0.4955479 
boosting RMSE 627 : 0.1495302 

forest 627 : -0.4376856 
forest mean 627 : -0.3855255 
forest RMSE 627 : 0.05455713 

nnet 627 : -0.492824 
nnet mean 627 : -0.4090511 
nnet RMSE 627 : 0.1415061 


s: 628 
logit 628 : -0.3905274 
logit mean 628 : -0.4378703 
logit RMSE 628 : 0.06822632 

boosting 628 : -0.5902239 
boosting mean 628 : -0.4956987 
boosting RMSE 628 : 0.1496038 

forest 628 : -0.3865627 
forest mean 628 : -0.3855271 
forest RMSE 628 : 0.05451631 

nnet 628 : -0.6201828 
nnet mean 628 : -0.4093873 
nnet RMSE 628 : 0.1416661 


s: 629 
logit 629 : -0.4030166 
logit mean 629 : -0.4378149 
logit RMSE 629 : 0.06817217 

boosting 629 : -0.4676055 
boosting mean 629 : -0.495654 
boosting RMSE 629 : 0.1495091 

forest 629 : -0.4193793 
forest mean 629 : -0.3855810 
forest RMSE 629 : 0.05447844 

nnet 629 : -0.3561071 
nnet mean 629 : -0.4093026 
nnet RMSE 629 : 0.1415642 


s: 630 
logit 630 : -0.356129 
logit mean 630 : -0.4376853 
logit RMSE 630 : 0.06814047 

boosting 630 : -0.3195619 
boosting mean 630 : -0.4953745 
boosting RMSE 630 : 0.1494248 

forest 630 : -0.3512315 
forest mean 630 : -0.3855264 
forest RMSE 630 : 0.05446985 

nnet 630 : -0.4412126 
nnet mean 630 : -0.4093532 
nnet RMSE 630 : 0.1414614 


s: 631 
logit 631 : -0.3729639 
logit mean 631 : -0.4375827 
logit RMSE 631 : 0.06809496 

boosting 631 : -0.4989677 
boosting mean 631 : -0.4953802 
boosting RMSE 631 : 0.1493583 

forest 631 : -0.3879436 
forest mean 631 : -0.3855303 
forest RMSE 631 : 0.05442878 

nnet 631 : -0.1439355 
nnet mean 631 : -0.4089326 
nnet RMSE 631 : 0.1417163 


s: 632 
logit 632 : -0.4323632 
logit mean 632 : -0.4375744 
logit RMSE 632 : 0.06805324 

boosting 632 : -0.625022 
boosting mean 632 : -0.4955853 
boosting RMSE 632 : 0.1495083 

forest 632 : -0.3438883 
forest mean 632 : -0.3854644 
forest RMSE 632 : 0.05443149 

nnet 632 : -0.3323556 
nnet mean 632 : -0.4088114 
nnet RMSE 632 : 0.1416297 


s: 633 
logit 633 : -0.5197826 
logit mean 633 : -0.4377043 
logit RMSE 633 : 0.06816593 

boosting 633 : -0.707133 
boosting mean 633 : -0.4959195 
boosting RMSE 633 : 0.1498881 

forest 633 : -0.3695059 
forest mean 633 : -0.3854392 
forest RMSE 633 : 0.05440198 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 633 : -0.2893319 
nnet mean 633 : -0.4086227 
nnet RMSE 633 : 0.1415862 


s: 634 
logit 634 : -0.4929203 
logit mean 634 : -0.4377914 
logit RMSE 634 : 0.06821205 

boosting 634 : -0.47419 
boosting mean 634 : -0.4958852 
boosting RMSE 634 : 0.1497988 

forest 634 : -0.3715305 
forest mean 634 : -0.3854172 
forest RMSE 634 : 0.05437082 

nnet 634 : -0.5638994 
nnet mean 634 : -0.4088676 
nnet RMSE 634 : 0.1416241 


s: 635 
logit 635 : -0.4798391 
logit mean 635 : -0.4378576 
logit RMSE 635 : 0.06823192 

boosting 635 : -0.5395173 
boosting mean 635 : -0.4959539 
boosting RMSE 635 : 0.1497832 

forest 635 : -0.3672533 
forest mean 635 : -0.3853886 
forest RMSE 635 : 0.05434353 

nnet 635 : -0.2711101 
nnet mean 635 : -0.4086506 
nnet RMSE 635 : 0.1416050 


s: 636 
logit 636 : -0.3648777 
logit mean 636 : -0.4377429 
logit RMSE 636 : 0.06819248 

boosting 636 : -0.4438566 
boosting mean 636 : -0.495872 
boosting RMSE 636 : 0.1496755 

forest 636 : -0.4126552 
forest mean 636 : -0.3854315 
forest RMSE 636 : 0.05430311 

nnet 636 : -0.3436482 
nnet mean 636 : -0.4085484 
nnet RMSE 636 : 0.1415112 


s: 637 
logit 637 : -0.3979965 
logit mean 637 : -0.4376805 
logit RMSE 637 : 0.06813897 

boosting 637 : -0.4385616 
boosting mean 637 : -0.4957821 
boosting RMSE 637 : 0.1495658 

forest 637 : -0.3454328 
forest mean 637 : -0.3853687 
forest RMSE 637 : 0.05430352 

nnet 637 : -0.3170046 
nnet mean 637 : -0.4084047 
nnet RMSE 637 : 0.1414384 


s: 638 
logit 638 : -0.4575619 
logit mean 638 : -0.4377116 
logit RMSE 638 : 0.06812368 

boosting 638 : -0.5229664 
boosting mean 638 : -0.4958247 
boosting RMSE 638 : 0.1495278 

forest 638 : -0.422818 
forest mean 638 : -0.3854274 
forest RMSE 638 : 0.05426847 

nnet 638 : -0.5980037 
nnet mean 638 : -0.4087019 
nnet RMSE 638 : 0.1415447 


s: 639 
logit 639 : -0.4279438 
logit mean 639 : -0.4376963 
logit RMSE 639 : 0.06807933 

boosting 639 : -0.714366 
boosting mean 639 : -0.4961667 
boosting RMSE 639 : 0.1499274 

forest 639 : -0.5075828 
forest mean 639 : -0.3856186 
forest RMSE 639 : 0.05439274 

nnet 639 : -0.5555878 
nnet mean 639 : -0.4089318 
nnet RMSE 639 : 0.1415678 


s: 640 
logit 640 : -0.4224588 
logit mean 640 : -0.4376725 
logit RMSE 640 : 0.06803192 

boosting 640 : -0.4499171 
boosting mean 640 : -0.4960944 
boosting RMSE 640 : 0.1498232 

forest 640 : -0.4328125 
forest mean 640 : -0.3856923 
forest RMSE 640 : 0.05436571 

nnet 640 : -0.4193844 
nnet mean 640 : -0.4089481 
nnet RMSE 640 : 0.1414592 


s: 641 
logit 641 : -0.4490754 
logit mean 641 : -0.4376903 
logit RMSE 641 : 0.06800646 

boosting 641 : -0.5039775 
boosting mean 641 : -0.4961067 
boosting RMSE 641 : 0.1497626 

forest 641 : -0.3981547 
forest mean 641 : -0.3857117 
forest RMSE 641 : 0.05432333 

nnet 641 : -0.5669667 
nnet mean 641 : -0.4091946 
nnet RMSE 641 : 0.1415026 


s: 642 
logit 642 : -0.3965272 
logit mean 642 : -0.4376262 
logit RMSE 642 : 0.06795361 

boosting 642 : -0.4699391 
boosting mean 642 : -0.496066 
boosting RMSE 642 : 0.1496714 

forest 642 : -0.3231428 
forest mean 642 : -0.3856143 
forest RMSE 642 : 0.05436569 

nnet 642 : -0.3615923 
nnet mean 642 : -0.4091205 
nnet RMSE 642 : 0.1414005 


s: 643 
logit 643 : -0.4190508 
logit mean 643 : -0.4375973 
logit RMSE 643 : 0.0679049 

boosting 643 : -0.6840501 
boosting mean 643 : -0.4963583 
boosting RMSE 643 : 0.1499739 

forest 643 : -0.3529536 
forest mean 643 : -0.3855635 
forest RMSE 643 : 0.05435508 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 643 : -0.1719870 
nnet mean 643 : -0.4087517 
nnet RMSE 643 : 0.1415763 


s: 644 
logit 644 : -0.4239498 
logit mean 644 : -0.4375761 
logit RMSE 644 : 0.06785873 

boosting 644 : -0.3643479 
boosting mean 644 : -0.4961533 
boosting RMSE 644 : 0.1498640 

forest 644 : -0.3414360 
forest mean 644 : -0.385495 
forest RMSE 644 : 0.05436186 

nnet 644 : -0.5361297 
nnet mean 644 : -0.4089495 
nnet RMSE 644 : 0.141568 


s: 645 
logit 645 : -0.3994562 
logit mean 645 : -0.437517 
logit RMSE 645 : 0.0678061 

boosting 645 : -0.5809895 
boosting mean 645 : -0.4962849 
boosting RMSE 645 : 0.1499172 

forest 645 : -0.4593819 
forest mean 645 : -0.3856095 
forest RMSE 645 : 0.05437001 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 645 : -0.2326463 
nnet mean 645 : -0.4086761 
nnet RMSE 645 : 0.1416116 


s: 646 
logit 646 : -0.4169472 
logit mean 646 : -0.4374852 
logit RMSE 646 : 0.06775689 

boosting 646 : -0.5266718 
boosting mean 646 : -0.4963319 
boosting RMSE 646 : 0.1498840 

forest 646 : -0.3989543 
forest mean 646 : -0.3856302 
forest RMSE 646 : 0.05432792 

nnet 646 : -0.3892687 
nnet mean 646 : -0.4086461 
nnet RMSE 646 : 0.1415026 


s: 647 
logit 647 : -0.4944204 
logit mean 647 : -0.4375732 
logit RMSE 647 : 0.06780619 

boosting 647 : -0.5839762 
boosting mean 647 : -0.4964674 
boosting RMSE 647 : 0.1499427 

forest 647 : -0.4608525 
forest mean 647 : -0.3857464 
forest RMSE 647 : 0.05433861 

nnet 647 : -0.3252490 
nnet mean 647 : -0.4085172 
nnet RMSE 647 : 0.1414237 


s: 648 
logit 648 : -0.4168056 
logit mean 648 : -0.4375411 
logit RMSE 648 : 0.06775706 

boosting 648 : -0.4589223 
boosting mean 648 : -0.4964094 
boosting RMSE 648 : 0.1498448 

forest 648 : -0.4057231 
forest mean 648 : -0.3857773 
forest RMSE 648 : 0.05429713 

nnet 648 : -0.2239766 
nnet mean 648 : -0.4082324 
nnet RMSE 648 : 0.1414837 


s: 649 
logit 649 : -0.3390556 
logit mean 649 : -0.4373894 
logit RMSE 649 : 0.0677471 

boosting 649 : -0.3911726 
boosting mean 649 : -0.4962473 
boosting RMSE 649 : 0.1497298 

forest 649 : -0.4913469 
forest mean 649 : -0.3859399 
forest RMSE 649 : 0.05437364 

nnet 649 : -0.4818806 
nnet mean 649 : -0.4083459 
nnet RMSE 649 : 0.1414111 


s: 650 
logit 650 : -0.4353721 
logit mean 650 : -0.4373863 
logit RMSE 650 : 0.06770918 

boosting 650 : -0.6136554 
boosting mean 650 : -0.4964279 
boosting RMSE 650 : 0.1498491 

forest 650 : -0.4036878 
forest mean 650 : -0.3859672 
forest RMSE 650 : 0.054332 

nnet 650 : -0.4610155 
nnet mean 650 : -0.4084269 
nnet RMSE 650 : 0.1413226 


s: 651 
logit 651 : -0.4672913 
logit mean 651 : -0.4374322 
logit RMSE 651 : 0.06770854 

boosting 651 : -0.6383885 
boosting mean 651 : -0.496646 
boosting RMSE 651 : 0.1500251 

forest 651 : -0.4586086 
forest mean 651 : -0.3860788 
forest RMSE 651 : 0.05433882 

nnet 651 : -0.5077776 
nnet mean 651 : -0.4085795 
nnet RMSE 651 : 0.1412772 


s: 652 
logit 652 : -0.5256951 
logit mean 652 : -0.4375676 
logit RMSE 652 : 0.06783544 

boosting 652 : -0.5667667 
boosting mean 652 : -0.4967535 
boosting RMSE 652 : 0.1500522 

forest 652 : -0.3076848 
forest mean 652 : -0.3859586 
forest RMSE 652 : 0.05441736 

nnet 652 : -0.5322494 
nnet mean 652 : -0.4087692 
nnet RMSE 652 : 0.1412638 


s: 653 
logit 653 : -0.4584095 
logit mean 653 : -0.4375995 
logit RMSE 653 : 0.067822 

boosting 653 : -0.3299545 
boosting mean 653 : -0.4964981 
boosting RMSE 653 : 0.1499624 

forest 653 : -0.4318226 
forest mean 653 : -0.3860288 
forest RMSE 653 : 0.05438994 

nnet 653 : -0.3192567 
nnet mean 653 : -0.4086321 
nnet RMSE 653 : 0.1411909 


s: 654 
logit 654 : -0.3587841 
logit mean 654 : -0.437479 
logit RMSE 654 : 0.0677893 

boosting 654 : -0.4302849 
boosting mean 654 : -0.4963968 
boosting RMSE 654 : 0.1498523 

forest 654 : -0.3406254 
forest mean 654 : -0.3859594 
forest RMSE 654 : 0.05439791 

nnet 654 : -0.3659942 
nnet mean 654 : -0.4085669 
nnet RMSE 654 : 0.1410892 


s: 655 
logit 655 : -0.3505894 
logit mean 655 : -0.4373463 
logit RMSE 655 : 0.06776503 

boosting 655 : -0.5548107 
boosting mean 655 : -0.496486 
boosting RMSE 655 : 0.1498600 

forest 655 : -0.3447812 
forest mean 655 : -0.3858965 
forest RMSE 655 : 0.05439917 

nnet 655 : -0.676772 
nnet mean 655 : -0.4089764 
nnet RMSE 655 : 0.1413956 


s: 656 
logit 656 : -0.3884569 
logit mean 656 : -0.4372718 
logit RMSE 656 : 0.06771486 

boosting 656 : -0.4578637 
boosting mean 656 : -0.4964271 
boosting RMSE 656 : 0.1497628 

forest 656 : -0.2750697 
forest mean 656 : -0.3857276 
forest RMSE 656 : 0.0545761 

nnet 656 : -0.4559731 
nnet mean 656 : -0.4090480 
nnet RMSE 656 : 0.1413047 


s: 657 
logit 657 : -0.4058126 
logit mean 657 : -0.4372239 
logit RMSE 657 : 0.06766369 

boosting 657 : -0.342384 
boosting mean 657 : -0.4961927 
boosting RMSE 657 : 0.1496657 

forest 657 : -0.4142031 
forest mean 657 : -0.3857709 
forest RMSE 657 : 0.05453737 

nnet 657 : -0.3416775 
nnet mean 657 : -0.4089455 
nnet RMSE 657 : 0.1412155 


s: 658 
logit 658 : -0.3603161 
logit mean 658 : -0.4371071 
logit RMSE 658 : 0.06762995 

boosting 658 : -0.2926296 
boosting mean 658 : -0.4958833 
boosting RMSE 658 : 0.1496105 

forest 658 : -0.2984798 
forest mean 658 : -0.3856383 
forest RMSE 658 : 0.05463943 

nnet 658 : -0.3487117 
nnet mean 658 : -0.408854 
nnet RMSE 658 : 0.1411223 


s: 659 
logit 659 : -0.4186115 
logit mean 659 : -0.437079 
logit RMSE 659 : 0.06758251 

boosting 659 : -0.3922085 
boosting mean 659 : -0.495726 
boosting RMSE 659 : 0.1494972 

forest 659 : -0.4444695 
forest mean 659 : -0.3857275 
forest RMSE 659 : 0.05462543 

nnet 659 : -0.2655614 
nnet mean 659 : -0.4086365 
nnet RMSE 659 : 0.1411124 


s: 660 
logit 660 : -0.3709375 
logit mean 660 : -0.4369788 
logit RMSE 660 : 0.06754076 

boosting 660 : -0.3802137 
boosting mean 660 : -0.495551 
boosting RMSE 660 : 0.1493859 

forest 660 : -0.4515166 
forest mean 660 : -0.3858272 
forest RMSE 660 : 0.05462086 

nnet 660 : -0.5347826 
nnet mean 660 : -0.4088277 
nnet RMSE 660 : 0.141103 


s: 661 
logit 661 : -0.3635774 
logit mean 661 : -0.4368677 
logit RMSE 661 : 0.06750452 

boosting 661 : -0.4535794 
boosting mean 661 : -0.4954875 
boosting RMSE 661 : 0.1492874 

forest 661 : -0.3278313 
forest mean 661 : -0.3857395 
forest RMSE 661 : 0.05465166 

nnet 661 : -0.4664501 
nnet mean 661 : -0.4089148 
nnet RMSE 661 : 0.1410199 


s: 662 
logit 662 : -0.4366861 
logit mean 662 : -0.4368675 
logit RMSE 662 : 0.06746859 

boosting 662 : -0.5231521 
boosting mean 662 : -0.4955293 
boosting RMSE 662 : 0.1492514 

forest 662 : -0.3210960 
forest mean 662 : -0.3856418 
forest RMSE 662 : 0.0546964 

nnet 662 : -0.2495290 
nnet mean 662 : -0.4086741 
nnet RMSE 662 : 0.1410347 


s: 663 
logit 663 : -0.439569 
logit mean 663 : -0.4368715 
logit RMSE 663 : 0.0674352 

boosting 663 : -0.5318943 
boosting mean 663 : -0.4955841 
boosting RMSE 663 : 0.1492267 

forest 663 : -0.4265502 
forest mean 663 : -0.3857035 
forest RMSE 663 : 0.05466487 

nnet 663 : 0.01775984 
nnet mean 663 : -0.4080309 
nnet RMSE 663 : 0.1418591 


s: 664 
logit 664 : -0.4026704 
logit mean 664 : -0.43682 
logit RMSE 664 : 0.06738448 

boosting 664 : -0.3693066 
boosting mean 664 : -0.4953939 
boosting RMSE 664 : 0.1491191 

forest 664 : -0.3055018 
forest mean 664 : -0.3855828 
forest RMSE 664 : 0.05474665 

nnet 664 : -0.2678735 
nnet mean 664 : -0.4078198 
nnet RMSE 664 : 0.1418450 


s: 665 
logit 665 : -0.3941529 
logit mean 665 : -0.4367559 
logit RMSE 665 : 0.06733418 

boosting 665 : -0.3096199 
boosting mean 665 : -0.4951146 
boosting RMSE 665 : 0.1490481 

forest 665 : -0.3376237 
forest mean 665 : -0.3855106 
forest RMSE 665 : 0.05475892 

nnet 665 : -0.2356486 
nnet mean 665 : -0.4075609 
nnet RMSE 665 : 0.1418815 


s: 666 
logit 666 : -0.5254125 
logit mean 666 : -0.436889 
logit RMSE 666 : 0.06745887 

boosting 666 : -0.4115239 
boosting mean 666 : -0.4949891 
boosting RMSE 666 : 0.1489369 

forest 666 : -0.3081007 
forest mean 666 : -0.3853944 
forest RMSE 666 : 0.05483355 

nnet 666 : -0.4685941 
nnet mean 666 : -0.4076525 
nnet RMSE 666 : 0.1417998 


s: 667 
logit 667 : -0.4219087 
logit mean 667 : -0.4368665 
logit RMSE 667 : 0.06741362 

boosting 667 : -0.3141169 
boosting mean 667 : -0.4947179 
boosting RMSE 667 : 0.1488623 

forest 667 : -0.3898973 
forest mean 667 : -0.3854012 
forest RMSE 667 : 0.05479383 

nnet 667 : -0.1128160 
nnet mean 667 : -0.4072105 
nnet RMSE 667 : 0.1421292 


s: 668 
logit 668 : -0.5150599 
logit mean 668 : -0.4369836 
logit RMSE 668 : 0.06751009 

boosting 668 : -0.4886668 
boosting mean 668 : -0.4947088 
boosting RMSE 668 : 0.1487904 

forest 668 : -0.3883545 
forest mean 668 : -0.3854056 
forest RMSE 668 : 0.05475465 

nnet 668 : -0.3163947 
nnet mean 668 : -0.4070745 
nnet RMSE 668 : 0.1420596 


s: 669 
logit 669 : -0.3747553 
logit mean 669 : -0.4368906 
logit RMSE 669 : 0.06746667 

boosting 669 : -0.5416158 
boosting mean 669 : -0.4947789 
boosting RMSE 669 : 0.1487799 

forest 669 : -0.4038095 
forest mean 669 : -0.3854331 
forest RMSE 669 : 0.05471391 

nnet 669 : -0.3951121 
nnet mean 669 : -0.4070567 
nnet RMSE 669 : 0.1419535 


s: 670 
logit 670 : -0.4593845 
logit mean 670 : -0.4369241 
logit RMSE 670 : 0.06745533 

boosting 670 : -0.4658071 
boosting mean 670 : -0.4947357 
boosting RMSE 670 : 0.1486906 

forest 670 : -0.4965886 
forest mean 670 : -0.385599 
forest RMSE 670 : 0.05480026 

nnet 670 : -0.6517876 
nnet mean 670 : -0.4074219 
nnet RMSE 670 : 0.1421807 


s: 671 
logit 671 : -0.4157775 
logit mean 671 : -0.4368926 
logit RMSE 671 : 0.0674078 

boosting 671 : -0.5280537 
boosting mean 671 : -0.4947853 
boosting RMSE 671 : 0.1486620 

forest 671 : -0.3403868 
forest mean 671 : -0.3855316 
forest RMSE 671 : 0.05480775 

nnet 671 : -0.5785255 
nnet mean 671 : -0.4076769 
nnet RMSE 671 : 0.1422417 


s: 672 
logit 672 : -0.3663412 
logit mean 672 : -0.4367876 
logit RMSE 672 : 0.06737014 

boosting 672 : -0.6416552 
boosting mean 672 : -0.4950039 
boosting RMSE 672 : 0.1488435 

forest 672 : -0.4052679 
forest mean 672 : -0.385561 
forest RMSE 672 : 0.05476733 

nnet 672 : -0.2880229 
nnet mean 672 : -0.4074989 
nnet RMSE 672 : 0.1422015 


s: 673 
logit 673 : -0.5364556 
logit mean 673 : -0.4369357 
logit RMSE 673 : 0.06752525 

boosting 673 : -0.5028751 
boosting mean 673 : -0.4950156 
boosting RMSE 673 : 0.1487858 

forest 673 : -0.4166540 
forest mean 673 : -0.3856072 
forest RMSE 673 : 0.05473039 

nnet 673 : -0.6114284 
nnet mean 673 : -0.4078019 
nnet RMSE 673 : 0.1423293 


s: 674 
logit 674 : -0.4237946 
logit mean 674 : -0.4369162 
logit RMSE 674 : 0.06748136 

boosting 674 : -0.340221 
boosting mean 674 : -0.4947859 
boosting RMSE 674 : 0.1486932 

forest 674 : -0.3041531 
forest mean 674 : -0.3854863 
forest RMSE 674 : 0.05481424 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 674 : -0.2552180 
nnet mean 674 : -0.4075755 
nnet RMSE 674 : 0.142333 


s: 675 
logit 675 : -0.3738613 
logit mean 675 : -0.4368228 
logit RMSE 675 : 0.06743886 

boosting 675 : -0.5122665 
boosting mean 675 : -0.4948118 
boosting RMSE 675 : 0.1486458 

forest 675 : -0.3742331 
forest mean 675 : -0.3854697 
forest RMSE 675 : 0.0547826 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 675 : -0.2635987 
nnet mean 675 : -0.4073622 
nnet RMSE 675 : 0.1423244 


s: 676 
logit 676 : -0.4328508 
logit mean 676 : -0.4368169 
logit RMSE 676 : 0.0674008 

boosting 676 : -0.5689063 
boosting mean 676 : -0.4949214 
boosting RMSE 676 : 0.1486778 

forest 676 : -0.4061548 
forest mean 676 : -0.3855003 
forest RMSE 676 : 0.05474258 

nnet 676 : -0.4121819 
nnet mean 676 : -0.4073693 
nnet RMSE 676 : 0.1422199 


s: 677 
logit 677 : -0.4882283 
logit mean 677 : -0.4368929 
logit RMSE 677 : 0.06743631 

boosting 677 : -0.5052071 
boosting mean 677 : -0.4949366 
boosting RMSE 677 : 0.148623 

forest 677 : -0.3659554 
forest mean 677 : -0.3854714 
forest RMSE 677 : 0.05471778 

nnet 677 : -0.2844809 
nnet mean 677 : -0.4071878 
nnet RMSE 677 : 0.1421841 


s: 678 
logit 678 : -0.3842338 
logit mean 678 : -0.4368152 
logit RMSE 678 : 0.06738928 

boosting 678 : -0.3614452 
boosting mean 678 : -0.4947397 
boosting RMSE 678 : 0.1485207 

forest 678 : -0.3722785 
forest mean 678 : -0.3854519 
forest RMSE 678 : 0.05468778 

nnet 678 : -0.374118 
nnet mean 678 : -0.4071390 
nnet RMSE 678 : 0.1420827 


s: 679 
logit 679 : -0.3596930 
logit mean 679 : -0.4367016 
logit RMSE 679 : 0.0673574 

boosting 679 : -0.641562 
boosting mean 679 : -0.494956 
boosting RMSE 679 : 0.1487006 

forest 679 : -0.4149623 
forest mean 679 : -0.3854954 
forest RMSE 679 : 0.05465051 

nnet 679 : -0.276459 
nnet mean 679 : -0.4069466 
nnet RMSE 679 : 0.1420572 


s: 680 
logit 680 : -0.4918023 
logit mean 680 : -0.4367827 
logit RMSE 680 : 0.06739986 

boosting 680 : -0.5938682 
boosting mean 680 : -0.4951014 
boosting RMSE 680 : 0.1487771 

forest 680 : -0.339801 
forest mean 680 : -0.3854282 
forest RMSE 680 : 0.05465908 

nnet 680 : -0.1838479 
nnet mean 680 : -0.4066185 
nnet RMSE 680 : 0.1421945 


s: 681 
logit 681 : -0.4537562 
logit mean 681 : -0.4368076 
logit RMSE 681 : 0.06738185 

boosting 681 : -0.2926733 
boosting mean 681 : -0.4948042 
boosting RMSE 681 : 0.1487247 

forest 681 : -0.3014965 
forest mean 681 : -0.3853049 
forest RMSE 681 : 0.05474921 

nnet 681 : -0.1760555 
nnet mean 681 : -0.4062799 
nnet RMSE 681 : 0.1423490 


s: 682 
logit 682 : -0.4363658 
logit mean 682 : -0.4368069 
logit RMSE 682 : 0.06734683 

boosting 682 : -0.3642622 
boosting mean 682 : -0.4946128 
boosting RMSE 682 : 0.1486219 

forest 682 : -0.2720179 
forest mean 682 : -0.3851388 
forest RMSE 682 : 0.05492812 

nnet 682 : -0.4462738 
nnet mean 682 : -0.4063386 
nnet RMSE 682 : 0.1422556 


s: 683 
logit 683 : -0.4401652 
logit mean 683 : -0.4368118 
logit RMSE 683 : 0.06731506 

boosting 683 : -0.3889111 
boosting mean 683 : -0.494458 
boosting RMSE 683 : 0.1485136 

forest 683 : -0.2440920 
forest mean 683 : -0.3849323 
forest RMSE 683 : 0.05521114 

nnet 683 : -0.7810156 
nnet mean 683 : -0.4068872 
nnet RMSE 683 : 0.1428971 


s: 684 
logit 684 : -0.3834022 
logit mean 684 : -0.4367338 
logit RMSE 684 : 0.06726883 

boosting 684 : -0.4320477 
boosting mean 684 : -0.4943668 
boosting RMSE 684 : 0.1484101 

forest 684 : -0.3859659 
forest mean 684 : -0.3849338 
forest RMSE 684 : 0.05517337 

nnet 684 : -0.6193627 
nnet mean 684 : -0.4071978 
nnet RMSE 684 : 0.1430387 


s: 685 
logit 685 : -0.5508728 
logit mean 685 : -0.4369004 
logit RMSE 685 : 0.06746643 

boosting 685 : -0.3463687 
boosting mean 685 : -0.4941507 
boosting RMSE 685 : 0.1483159 

forest 685 : -0.3848111 
forest mean 685 : -0.3849337 
forest RMSE 685 : 0.05513614 

nnet 685 : -0.3036784 
nnet mean 685 : -0.4070467 
nnet RMSE 685 : 0.1429816 


s: 686 
logit 686 : -0.4538137 
logit mean 686 : -0.436925 
logit RMSE 686 : 0.06744854 

boosting 686 : -0.4503448 
boosting mean 686 : -0.4940869 
boosting RMSE 686 : 0.1482202 

forest 686 : -0.3941616 
forest mean 686 : -0.3849471 
forest RMSE 686 : 0.05509639 

nnet 686 : -0.2210108 
nnet mean 686 : -0.4067755 
nnet RMSE 686 : 0.1430407 


s: 687 
logit 687 : -0.4437658 
logit mean 687 : -0.436935 
logit RMSE 687 : 0.06742011 

boosting 687 : -0.3493702 
boosting mean 687 : -0.4938762 
boosting RMSE 687 : 0.1481249 

forest 687 : -0.300339 
forest mean 687 : -0.3848240 
forest RMSE 687 : 0.05518742 

nnet 687 : -0.4051497 
nnet mean 687 : -0.4067731 
nnet RMSE 687 : 0.1429367 


s: 688 
logit 688 : -0.5048852 
logit mean 688 : -0.4370338 
logit RMSE 688 : 0.06748966 

boosting 688 : -0.5156861 
boosting mean 688 : -0.4939079 
boosting RMSE 688 : 0.1480829 

forest 688 : -0.3803457 
forest mean 688 : -0.3848174 
forest RMSE 688 : 0.05515239 

nnet 688 : -0.4565679 
nnet mean 688 : -0.4068455 
nnet RMSE 688 : 0.1428491 


s: 689 
logit 689 : -0.4565469 
logit mean 689 : -0.4370621 
logit RMSE 689 : 0.06747507 

boosting 689 : -0.4029588 
boosting mean 689 : -0.4937759 
boosting RMSE 689 : 0.1479754 

forest 689 : -0.4152315 
forest mean 689 : -0.3848616 
forest RMSE 689 : 0.0551154 

nnet 689 : -0.5633513 
nnet mean 689 : -0.4070726 
nnet RMSE 689 : 0.1428810 


s: 690 
logit 690 : -0.3461171 
logit mean 690 : -0.4369303 
logit RMSE 690 : 0.06745735 

boosting 690 : -0.4686426 
boosting mean 690 : -0.4937395 
boosting RMSE 690 : 0.1478913 

forest 690 : -0.3217629 
forest mean 690 : -0.3847701 
forest RMSE 690 : 0.05515593 

nnet 690 : -0.4577844 
nnet mean 690 : -0.4071461 
nnet RMSE 690 : 0.1427943 


s: 691 
logit 691 : -0.3876147 
logit mean 691 : -0.4368589 
logit RMSE 691 : 0.06741017 

boosting 691 : -0.4220483 
boosting mean 691 : -0.4936357 
boosting RMSE 691 : 0.1477866 

forest 691 : -0.4161169 
forest mean 691 : -0.3848155 
forest RMSE 691 : 0.05511941 

nnet 691 : -0.4285129 
nnet mean 691 : -0.4071771 
nnet RMSE 691 : 0.1426951 


s: 692 
logit 692 : -0.4278828 
logit mean 692 : -0.4368459 
logit RMSE 692 : 0.06736978 

boosting 692 : -0.5409649 
boosting mean 692 : -0.4937041 
boosting RMSE 692 : 0.1477770 

forest 692 : -0.4208477 
forest mean 692 : -0.3848676 
forest RMSE 692 : 0.05508527 

nnet 692 : -0.6394215 
nnet mean 692 : -0.4075127 
nnet RMSE 692 : 0.1428821 


s: 693 
logit 693 : -0.4489318 
logit mean 693 : -0.4368634 
logit RMSE 693 : 0.06734681 

boosting 693 : -0.7267008 
boosting mean 693 : -0.4940403 
boosting RMSE 693 : 0.1481909 

forest 693 : -0.4415391 
forest mean 693 : -0.3849493 
forest RMSE 693 : 0.05506813 

nnet 693 : -0.4323019 
nnet mean 693 : -0.4075484 
nnet RMSE 693 : 0.1427843 


s: 694 
logit 694 : -0.4173617 
logit mean 694 : -0.4368353 
logit RMSE 694 : 0.0673015 

boosting 694 : -0.5677455 
boosting mean 694 : -0.4941465 
boosting RMSE 694 : 0.1482209 

forest 694 : -0.3487944 
forest mean 694 : -0.3848973 
forest RMSE 694 : 0.05506275 

nnet 694 : -0.2726465 
nnet mean 694 : -0.4073541 
nnet RMSE 694 : 0.1427632 


s: 695 
logit 695 : -0.401107 
logit mean 695 : -0.4367839 
logit RMSE 695 : 0.06725308 

boosting 695 : -0.3859756 
boosting mean 695 : -0.4939909 
boosting RMSE 695 : 0.1481152 

forest 695 : -0.3973771 
forest mean 695 : -0.3849152 
forest RMSE 695 : 0.05502322 

nnet 695 : -0.4020103 
nnet mean 695 : -0.4073464 
nnet RMSE 695 : 0.1426605 


s: 696 
logit 696 : -0.4007314 
logit mean 696 : -0.4367321 
logit RMSE 696 : 0.06720475 

boosting 696 : -0.3468777 
boosting mean 696 : -0.4937795 
boosting RMSE 696 : 0.1480224 

forest 696 : -0.4304196 
forest mean 696 : -0.3849806 
forest RMSE 696 : 0.05499576 

nnet 696 : -0.09477566 
nnet mean 696 : -0.4068973 
nnet RMSE 696 : 0.1430267 


s: 697 
logit 697 : -0.3806604 
logit mean 697 : -0.4366516 
logit RMSE 697 : 0.06716052 

boosting 697 : -0.5096332 
boosting mean 697 : -0.4938023 
boosting RMSE 697 : 0.1479745 

forest 697 : -0.4105531 
forest mean 697 : -0.3850173 
forest RMSE 697 : 0.05495775 

nnet 697 : -0.6825257 
nnet mean 697 : -0.4072927 
nnet RMSE 697 : 0.1433241 


s: 698 
logit 698 : -0.4738788 
logit mean 698 : -0.436705 
logit RMSE 698 : 0.06717063 

boosting 698 : -0.4791233 
boosting mean 698 : -0.4937812 
boosting RMSE 698 : 0.1478988 

forest 698 : -0.3816699 
forest mean 698 : -0.3850125 
forest RMSE 698 : 0.05492275 

nnet 698 : -0.3929274 
nnet mean 698 : -0.4072721 
nnet RMSE 698 : 0.1432217 


s: 699 
logit 699 : -0.4351041 
logit mean 699 : -0.4367027 
logit RMSE 699 : 0.0671357 

boosting 699 : -0.4598563 
boosting mean 699 : -0.4937327 
boosting RMSE 699 : 0.1478103 

forest 699 : -0.3799555 
forest mean 699 : -0.3850052 
forest RMSE 699 : 0.05488869 

nnet 699 : -0.4028412 
nnet mean 699 : -0.4072658 
nnet RMSE 699 : 0.1431192 


s: 700 
logit 700 : -0.3926099 
logit mean 700 : -0.4366397 
logit RMSE 700 : 0.0670883 

boosting 700 : -0.4487039 
boosting mean 700 : -0.4936684 
boosting RMSE 700 : 0.1477162 

forest 700 : -0.4225678 
forest mean 700 : -0.3850589 
forest RMSE 700 : 0.0548561 

nnet 700 : -0.6766007 
nnet mean 700 : -0.4076506 
nnet RMSE 700 : 0.1433986 


s: 701 
logit 701 : -0.436432 
logit mean 701 : -0.4366394 
logit RMSE 701 : 0.06705456 

boosting 701 : -0.4925213 
boosting mean 701 : -0.4936668 
boosting RMSE 701 : 0.1476521 

forest 701 : -0.353229 
forest mean 701 : -0.3850135 
forest RMSE 701 : 0.05484541 

nnet 701 : -0.5410964 
nnet mean 701 : -0.4078409 
nnet RMSE 701 : 0.1433953 


s: 702 
logit 702 : -0.4185112 
logit mean 702 : -0.4366136 
logit RMSE 702 : 0.06701042 

boosting 702 : -0.7193051 
boosting mean 702 : -0.4939882 
boosting RMSE 702 : 0.1480383 

forest 702 : -0.3830887 
forest mean 702 : -0.3850108 
forest RMSE 702 : 0.05481005 

nnet 702 : -0.2180902 
nnet mean 702 : -0.4075706 
nnet RMSE 702 : 0.1434575 


s: 703 
logit 703 : -0.5007501 
logit mean 703 : -0.4367048 
logit RMSE 703 : 0.06707047 

boosting 703 : -0.6003312 
boosting mean 703 : -0.4941394 
boosting RMSE 703 : 0.1481258 

forest 703 : -0.4989796 
forest mean 703 : -0.3851729 
forest RMSE 703 : 0.05489813 

nnet 703 : -0.491519 
nnet mean 703 : -0.4076900 
nnet RMSE 703 : 0.143397 


s: 704 
logit 704 : -0.3995033 
logit mean 704 : -0.4366520 
logit RMSE 704 : 0.06702282 

boosting 704 : -0.4080019 
boosting mean 704 : -0.4940171 
boosting RMSE 704 : 0.1480208 

forest 704 : -0.3517979 
forest mean 704 : -0.3851255 
forest RMSE 704 : 0.0548892 

nnet 704 : -0.5185518 
nnet mean 704 : -0.4078475 
nnet RMSE 704 : 0.1433648 


s: 705 
logit 705 : -0.3414352 
logit mean 705 : -0.4365169 
logit RMSE 705 : 0.06701158 

boosting 705 : -0.6290466 
boosting mean 705 : -0.4942086 
boosting RMSE 705 : 0.1481671 

forest 705 : -0.3228756 
forest mean 705 : -0.3850372 
forest RMSE 705 : 0.05492711 

nnet 705 : -0.1234232 
nnet mean 705 : -0.4074441 
nnet RMSE 705 : 0.1436412 


s: 706 
logit 706 : -0.3749137 
logit mean 706 : -0.4364296 
logit RMSE 706 : 0.06697076 

boosting 706 : -0.5191383 
boosting mean 706 : -0.4942439 
boosting RMSE 706 : 0.1481300 

forest 706 : -0.3055086 
forest mean 706 : -0.3849245 
forest RMSE 706 : 0.05500328 

nnet 706 : -0.50537 
nnet mean 706 : -0.4075828 
nnet RMSE 706 : 0.1435942 


s: 707 
logit 707 : -0.3754079 
logit mean 707 : -0.4363433 
logit RMSE 707 : 0.06692977 

boosting 707 : -0.3315001 
boosting mean 707 : -0.4940137 
boosting RMSE 707 : 0.1480477 

forest 707 : -0.3815935 
forest mean 707 : -0.3849198 
forest RMSE 707 : 0.05496873 

nnet 707 : -0.3436754 
nnet mean 707 : -0.4074924 
nnet RMSE 707 : 0.1435083 


s: 708 
logit 708 : -0.3396356 
logit mean 708 : -0.4362067 
logit RMSE 708 : 0.06692095 

boosting 708 : -0.3139225 
boosting mean 708 : -0.4937594 
boosting RMSE 708 : 0.1479784 

forest 708 : -0.3844916 
forest mean 708 : -0.3849192 
forest RMSE 708 : 0.05493299 

nnet 708 : -0.3143987 
nnet mean 708 : -0.4073609 
nnet RMSE 708 : 0.143443 


s: 709 
logit 709 : -0.411634 
logit mean 709 : -0.4361721 
logit RMSE 709 : 0.06687517 

boosting 709 : -0.3923163 
boosting mean 709 : -0.4936163 
boosting RMSE 709 : 0.1478743 

forest 709 : -0.3130583 
forest mean 709 : -0.3848179 
forest RMSE 709 : 0.05499125 

nnet 709 : -0.4625644 
nnet mean 709 : -0.4074388 
nnet RMSE 709 : 0.1433611 


s: 710 
logit 710 : -0.3824951 
logit mean 710 : -0.4360965 
logit RMSE 710 : 0.06683129 

boosting 710 : -0.5914114 
boosting mean 710 : -0.493754 
boosting RMSE 710 : 0.1479447 

forest 710 : -0.4182336 
forest mean 710 : -0.3848649 
forest RMSE 710 : 0.05495678 

nnet 710 : -0.6564831 
nnet mean 710 : -0.4077895 
nnet RMSE 710 : 0.1435831 


s: 711 
logit 711 : -0.421106 
logit mean 711 : -0.4360754 
logit RMSE 711 : 0.06678896 

boosting 711 : -0.6802508 
boosting mean 711 : -0.4940163 
boosting RMSE 711 : 0.1482137 

forest 711 : -0.4340137 
forest mean 711 : -0.3849340 
forest RMSE 711 : 0.05493293 

nnet 711 : -0.2272919 
nnet mean 711 : -0.4075357 
nnet RMSE 711 : 0.1436282 


s: 712 
logit 712 : -0.5204973 
logit mean 712 : -0.436194 
logit RMSE 712 : 0.06689464 

boosting 712 : -0.5732725 
boosting mean 712 : -0.4941277 
boosting RMSE 712 : 0.1482519 

forest 712 : -0.4277442 
forest mean 712 : -0.3849942 
forest RMSE 712 : 0.05490418 

nnet 712 : -0.4035813 
nnet mean 712 : -0.4075301 
nnet RMSE 712 : 0.1435273 


s: 713 
logit 713 : -0.411784 
logit mean 713 : -0.4361597 
logit RMSE 713 : 0.06684917 

boosting 713 : -0.3923313 
boosting mean 713 : -0.4939849 
boosting RMSE 713 : 0.1481481 

forest 713 : -0.4168121 
forest mean 713 : -0.3850388 
forest RMSE 713 : 0.05486928 

nnet 713 : -0.5604021 
nnet mean 713 : -0.4077445 
nnet RMSE 713 : 0.1435524 


s: 714 
logit 714 : -0.4146683 
logit mean 714 : -0.4361296 
logit RMSE 714 : 0.0668046 

boosting 714 : -0.5247141 
boosting mean 714 : -0.4940279 
boosting RMSE 714 : 0.1481179 

forest 714 : -0.3929983 
forest mean 714 : -0.3850499 
forest RMSE 714 : 0.05483147 

nnet 714 : -0.2650615 
nnet mean 714 : -0.4075447 
nnet RMSE 714 : 0.1435407 


s: 715 
logit 715 : -0.4032790 
logit mean 715 : -0.4360837 
logit RMSE 715 : 0.06675798 

boosting 715 : -0.498264 
boosting mean 715 : -0.4940338 
boosting RMSE 715 : 0.1480599 

forest 715 : -0.3764351 
forest mean 715 : -0.3850379 
forest RMSE 715 : 0.0548002 

nnet 715 : -0.3778812 
nnet mean 715 : -0.4075032 
nnet RMSE 715 : 0.1434427 


s: 716 
logit 716 : -0.533835 
logit mean 716 : -0.4362202 
logit RMSE 716 : 0.06689858 

boosting 716 : -0.5422766 
boosting mean 716 : -0.4941012 
boosting RMSE 716 : 0.148052 

forest 716 : -0.4847651 
forest mean 716 : -0.3851772 
forest RMSE 716 : 0.05485346 

nnet 716 : -0.5161881 
nnet mean 716 : -0.407655 
nnet RMSE 716 : 0.1434082 


s: 717 
logit 717 : -0.4755778 
logit mean 717 : -0.4362751 
logit RMSE 717 : 0.06691147 

boosting 717 : -0.5910803 
boosting mean 717 : -0.4942365 
boosting RMSE 717 : 0.1481207 

forest 717 : -0.3594049 
forest mean 717 : -0.3851412 
forest RMSE 717 : 0.05483616 

nnet 717 : -0.5031157 
nnet mean 717 : -0.4077881 
nnet RMSE 717 : 0.1433599 


s: 718 
logit 718 : -0.4702541 
logit mean 718 : -0.4363224 
logit RMSE 718 : 0.06691624 

boosting 718 : -0.5139898 
boosting mean 718 : -0.494264 
boosting RMSE 718 : 0.1480786 

forest 718 : -0.414985 
forest mean 718 : -0.3851828 
forest RMSE 718 : 0.05480081 

nnet 718 : -0.2944544 
nnet mean 718 : -0.4076303 
nnet RMSE 718 : 0.1433142 


s: 719 
logit 719 : -0.4978674 
logit mean 719 : -0.436408 
logit RMSE 719 : 0.06696922 

boosting 719 : -0.629267 
boosting mean 719 : -0.4944518 
boosting RMSE 719 : 0.1482225 

forest 719 : -0.3582545 
forest mean 719 : -0.3851453 
forest RMSE 719 : 0.05478482 

nnet 719 : -0.2688119 
nnet mean 719 : -0.4074372 
nnet RMSE 719 : 0.1432980 


s: 720 
logit 720 : -0.4196424 
logit mean 720 : -0.4363847 
logit RMSE 720 : 0.0669267 

boosting 720 : -0.4331287 
boosting mean 720 : -0.4943666 
boosting RMSE 720 : 0.1481246 

forest 720 : -0.3834803 
forest mean 720 : -0.385143 
forest RMSE 720 : 0.05475022 

nnet 720 : -0.3703653 
nnet mean 720 : -0.4073857 
nnet RMSE 720 : 0.1432027 


s: 721 
logit 721 : -0.4110843 
logit mean 721 : -0.4363496 
logit RMSE 721 : 0.06688155 

boosting 721 : -0.3816050 
boosting mean 721 : -0.4942102 
boosting RMSE 721 : 0.1480235 

forest 721 : -0.4315026 
forest mean 721 : -0.3852073 
forest RMSE 721 : 0.05472482 

nnet 721 : -0.4198823 
nnet mean 721 : -0.4074031 
nnet RMSE 721 : 0.1431053 


s: 722 
logit 722 : -0.4281714 
logit mean 722 : -0.4363383 
logit RMSE 722 : 0.06684344 

boosting 722 : -0.5000729 
boosting mean 722 : -0.4942183 
boosting RMSE 722 : 0.1479678 

forest 722 : -0.4362681 
forest mean 722 : -0.3852781 
forest RMSE 722 : 0.05470356 

nnet 722 : -0.2606862 
nnet mean 722 : -0.4071998 
nnet RMSE 722 : 0.1431001 


s: 723 
logit 723 : -0.491395 
logit mean 723 : -0.4364145 
logit RMSE 723 : 0.06688362 

boosting 723 : -0.4983377 
boosting mean 723 : -0.494224 
boosting RMSE 723 : 0.1479106 

forest 723 : -0.4056603 
forest mean 723 : -0.3853062 
forest RMSE 723 : 0.05466612 

nnet 723 : -0.3628099 
nnet mean 723 : -0.4071384 
nnet RMSE 723 : 0.1430078 


s: 724 
logit 724 : -0.4776511 
logit mean 724 : -0.4364714 
logit RMSE 724 : 0.06689968 

boosting 724 : -0.4073999 
boosting mean 724 : -0.4941041 
boosting RMSE 724 : 0.1478087 

forest 724 : -0.4274063 
forest mean 724 : -0.3853644 
forest RMSE 724 : 0.05463785 

nnet 724 : -0.3259730 
nnet mean 724 : -0.4070263 
nnet RMSE 724 : 0.1429355 


s: 725 
logit 725 : -0.5497985 
logit mean 725 : -0.4366277 
logit RMSE 725 : 0.06708462 

boosting 725 : -0.5852077 
boosting mean 725 : -0.4942297 
boosting RMSE 725 : 0.1478668 

forest 725 : -0.393168 
forest mean 725 : -0.3853752 
forest RMSE 725 : 0.05460074 

nnet 725 : -0.5226724 
nnet mean 725 : -0.4071859 
nnet RMSE 725 : 0.1429095 


s: 726 
logit 726 : -0.4900054 
logit mean 726 : -0.4367013 
logit RMSE 726 : 0.06712157 

boosting 726 : -0.458693 
boosting mean 726 : -0.4941808 
boosting RMSE 726 : 0.147781 

forest 726 : -0.4753221 
forest mean 726 : -0.3854991 
forest RMSE 726 : 0.05463469 

nnet 726 : -0.3740402 
nnet mean 726 : -0.4071402 
nnet RMSE 726 : 0.1428143 


s: 727 
logit 727 : -0.4293505 
logit mean 727 : -0.4366911 
logit RMSE 727 : 0.06708422 

boosting 727 : -0.4955485 
boosting mean 727 : -0.4941827 
boosting RMSE 727 : 0.1477218 

forest 727 : -0.386764 
forest mean 727 : -0.3855008 
forest RMSE 727 : 0.05459931 

nnet 727 : -0.6914281 
nnet mean 727 : -0.4075312 
nnet RMSE 727 : 0.1431248 


s: 728 
logit 728 : -0.4764521 
logit mean 728 : -0.4367458 
logit RMSE 728 : 0.06709799 

boosting 728 : -0.4054767 
boosting mean 728 : -0.4940608 
boosting RMSE 728 : 0.1476205 

forest 728 : -0.3498218 
forest mean 728 : -0.3854518 
forest RMSE 728 : 0.05459348 

nnet 728 : -0.4362711 
nnet mean 728 : -0.4075707 
nnet RMSE 728 : 0.1430328 


s: 729 
logit 729 : -0.3342004 
logit mean 729 : -0.4366051 
logit RMSE 729 : 0.06709623 

boosting 729 : -0.5199557 
boosting mean 729 : -0.4940963 
boosting RMSE 729 : 0.1475861 

forest 729 : -0.3227918 
forest mean 729 : -0.3853658 
forest RMSE 729 : 0.05463092 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 729 : -0.2660355 
nnet mean 729 : -0.4073766 
nnet RMSE 729 : 0.1430207 


s: 730 
logit 730 : -0.3730984 
logit mean 730 : -0.4365181 
logit RMSE 730 : 0.06705765 

boosting 730 : -0.4382394 
boosting mean 730 : -0.4940198 
boosting RMSE 730 : 0.1474918 

forest 730 : -0.4083624 
forest mean 730 : -0.3853973 
forest RMSE 730 : 0.05459436 

nnet 730 : -0.4042569 
nnet mean 730 : -0.4073723 
nnet RMSE 730 : 0.1429228 


s: 731 
logit 731 : -0.4381896 
logit mean 731 : -0.4365204 
logit RMSE 731 : 0.06702665 

boosting 731 : -0.3835981 
boosting mean 731 : -0.4938688 
boosting RMSE 731 : 0.1473921 

forest 731 : -0.3568542 
forest mean 731 : -0.3853583 
forest RMSE 731 : 0.05458034 

nnet 731 : -0.4812641 
nnet mean 731 : -0.4074734 
nnet RMSE 731 : 0.1428566 


s: 732 
logit 732 : -0.482817 
logit mean 732 : -0.4365836 
logit RMSE 732 : 0.06705076 

boosting 732 : -0.3615929 
boosting mean 732 : -0.4936881 
boosting RMSE 732 : 0.1472982 

forest 732 : -0.4438231 
forest mean 732 : -0.3854382 
forest RMSE 732 : 0.05456709 

nnet 732 : -0.3295111 
nnet mean 732 : -0.4073669 
nnet RMSE 732 : 0.1427828 


s: 733 
logit 733 : -0.4678375 
logit mean 733 : -0.4366263 
logit RMSE 733 : 0.06705184 

boosting 733 : -0.5463508 
boosting mean 733 : -0.4937599 
boosting RMSE 733 : 0.1472969 

forest 733 : -0.3837678 
forest mean 733 : -0.3854359 
forest RMSE 733 : 0.05453315 

nnet 733 : -0.3549555 
nnet mean 733 : -0.4072954 
nnet RMSE 733 : 0.1426951 


s: 734 
logit 734 : -0.4243792 
logit mean 734 : -0.4366096 
logit RMSE 734 : 0.06701219 

boosting 734 : -0.5493419 
boosting mean 734 : -0.4938356 
boosting RMSE 734 : 0.1472997 

forest 734 : -0.4777518 
forest mean 734 : -0.3855616 
forest RMSE 734 : 0.05457151 

nnet 734 : -0.4983507 
nnet mean 734 : -0.4074194 
nnet RMSE 734 : 0.1426440 


s: 735 
logit 735 : -0.3864322 
logit mean 735 : -0.4365413 
logit RMSE 735 : 0.06696845 

boosting 735 : -0.5239369 
boosting mean 735 : -0.4938766 
boosting RMSE 735 : 0.1472705 

forest 735 : -0.3856198 
forest mean 735 : -0.3855617 
forest RMSE 735 : 0.05453695 

nnet 735 : -0.4216915 
nnet mean 735 : -0.4074388 
nnet RMSE 735 : 0.1425492 


s: 736 
logit 736 : -0.5152905 
logit mean 736 : -0.4366483 
logit RMSE 736 : 0.06705774 

boosting 736 : -0.5281647 
boosting mean 736 : -0.4939232 
boosting RMSE 736 : 0.1472462 

forest 736 : -0.4125209 
forest mean 736 : -0.3855984 
forest RMSE 736 : 0.05450184 

nnet 736 : -0.5309907 
nnet mean 736 : -0.4076067 
nnet RMSE 736 : 0.1425341 


s: 737 
logit 737 : -0.3935821 
logit mean 737 : -0.4365899 
logit RMSE 737 : 0.06701264 

boosting 737 : -0.3050795 
boosting mean 737 : -0.4936670 
boosting RMSE 737 : 0.1471878 

forest 737 : -0.3259777 
forest mean 737 : -0.3855175 
forest RMSE 737 : 0.05453306 

nnet 737 : -0.3959338 
nnet mean 737 : -0.4075909 
nnet RMSE 737 : 0.1424375 


s: 738 
logit 738 : -0.4653007 
logit mean 738 : -0.4366288 
logit RMSE 738 : 0.06701035 

boosting 738 : -0.5020182 
boosting mean 738 : -0.4936783 
boosting RMSE 738 : 0.1471360 

forest 738 : -0.3743744 
forest mean 738 : -0.3855024 
forest RMSE 738 : 0.05450427 

nnet 738 : -0.1953650 
nnet mean 738 : -0.4073033 
nnet RMSE 738 : 0.1425401 


s: 739 
logit 739 : -0.3806515 
logit mean 739 : -0.436553 
logit RMSE 739 : 0.06696878 

boosting 739 : -0.4332833 
boosting mean 739 : -0.4935965 
boosting RMSE 739 : 0.1470415 

forest 739 : -0.3803143 
forest mean 739 : -0.3854953 
forest RMSE 739 : 0.05447219 

nnet 739 : -0.3681265 
nnet mean 739 : -0.4072503 
nnet RMSE 739 : 0.1424485 


s: 740 
logit 740 : -0.4128723 
logit mean 740 : -0.436521 
logit RMSE 740 : 0.06692519 

boosting 740 : -0.2201364 
boosting mean 740 : -0.493227 
boosting RMSE 740 : 0.1470908 

forest 740 : -0.3777816 
forest mean 740 : -0.3854849 
forest RMSE 740 : 0.0544415 

nnet 740 : -0.413319 
nnet mean 740 : -0.4072585 
nnet RMSE 740 : 0.1423530 


s: 741 
logit 741 : -0.3853919 
logit mean 741 : -0.436452 
logit RMSE 741 : 0.06688217 

boosting 741 : -0.5299968 
boosting mean 741 : -0.4932766 
boosting RMSE 741 : 0.1470691 

forest 741 : -0.4311942 
forest mean 741 : -0.3855466 
forest RMSE 741 : 0.05441682 

nnet 741 : -0.3853395 
nnet mean 741 : -0.4072289 
nnet RMSE 741 : 0.1422580 


s: 742 
logit 742 : -0.4560929 
logit mean 742 : -0.4364785 
logit RMSE 742 : 0.0668688 

boosting 742 : -0.3298039 
boosting mean 742 : -0.4930563 
boosting RMSE 742 : 0.1469925 

forest 742 : -0.3213168 
forest mean 742 : -0.3854600 
forest RMSE 742 : 0.0544568 

nnet 742 : -0.5495056 
nnet mean 742 : -0.4074207 
nnet RMSE 742 : 0.1422680 


s: 743 
logit 743 : -0.4230733 
logit mean 743 : -0.4364605 
logit RMSE 743 : 0.06682915 

boosting 743 : -0.5727755 
boosting mean 743 : -0.4931636 
boosting RMSE 743 : 0.1470302 

forest 743 : -0.4275081 
forest mean 743 : -0.3855166 
forest RMSE 743 : 0.0544295 

nnet 743 : -0.2382281 
nnet mean 743 : -0.4071929 
nnet RMSE 743 : 0.1422960 


s: 744 
logit 744 : -0.4674686 
logit mean 744 : -0.4365021 
logit RMSE 744 : 0.06683001 

boosting 744 : -0.4253461 
boosting mean 744 : -0.4930724 
boosting RMSE 744 : 0.1469343 

forest 744 : -0.3692555 
forest mean 744 : -0.3854948 
forest RMSE 744 : 0.05440459 

nnet 744 : -0.3852627 
nnet mean 744 : -0.4071635 
nnet RMSE 744 : 0.1422014 


s: 745 
logit 745 : -0.3970858 
logit mean 745 : -0.4364492 
logit RMSE 745 : 0.06678523 

boosting 745 : -0.5586948 
boosting mean 745 : -0.4931605 
boosting RMSE 745 : 0.1469508 

forest 745 : -0.3598025 
forest mean 745 : -0.3854603 
forest RMSE 745 : 0.054388 

nnet 745 : -0.4907604 
nnet mean 745 : -0.4072757 
nnet RMSE 745 : 0.1421448 


s: 746 
logit 746 : -0.4806397 
logit mean 746 : -0.4365085 
logit RMSE 746 : 0.06680572 

boosting 746 : -0.3899698 
boosting mean 746 : -0.4930222 
boosting RMSE 746 : 0.1468527 

forest 746 : -0.414383 
forest mean 746 : -0.3854991 
forest RMSE 746 : 0.05435409 

nnet 746 : -0.09664172 
nnet mean 746 : -0.4068593 
nnet RMSE 746 : 0.1424831 


s: 747 
logit 747 : -0.4176266 
logit mean 747 : -0.4364832 
logit RMSE 747 : 0.06676411 

boosting 747 : -0.6627095 
boosting mean 747 : -0.4932494 
boosting RMSE 747 : 0.1470688 

forest 747 : -0.4095728 
forest mean 747 : -0.3855313 
forest RMSE 747 : 0.05431882 

nnet 747 : -0.3040984 
nnet mean 747 : -0.4067217 
nnet RMSE 747 : 0.1424309 


s: 748 
logit 748 : -0.3205441 
logit mean 748 : -0.4363282 
logit RMSE 748 : 0.06678269 

boosting 748 : -0.5951779 
boosting mean 748 : -0.4933856 
boosting RMSE 748 : 0.1471436 

forest 748 : -0.3462222 
forest mean 748 : -0.3854787 
forest RMSE 748 : 0.0543181 

nnet 748 : -0.5255145 
nnet mean 748 : -0.4068805 
nnet RMSE 748 : 0.1424096 


s: 749 
logit 749 : -0.5938761 
logit mean 749 : -0.4365385 
logit RMSE 749 : 0.06711301 

boosting 749 : -0.5027456 
boosting mean 749 : -0.4933981 
boosting RMSE 749 : 0.1470933 

forest 749 : -0.4052504 
forest mean 749 : -0.3855051 
forest RMSE 749 : 0.05428217 

nnet 749 : -0.3323865 
nnet mean 749 : -0.4067811 
nnet RMSE 749 : 0.1423360 


s: 750 
logit 750 : -0.3843548 
logit mean 750 : -0.436469 
logit RMSE 750 : 0.06707069 

boosting 750 : -0.4437727 
boosting mean 750 : -0.493332 
boosting RMSE 750 : 0.1470039 

forest 750 : -0.3264 
forest mean 750 : -0.3854263 
forest RMSE 750 : 0.0543125 

nnet 750 : -0.3391242 
nnet mean 750 : -0.4066909 
nnet RMSE 750 : 0.1422584 


s: 751 
logit 751 : -0.3833485 
logit mean 751 : -0.4363982 
logit RMSE 751 : 0.06702878 

boosting 751 : -0.5621523 
boosting mean 751 : -0.4934236 
boosting RMSE 751 : 0.1470251 

forest 751 : -0.4689166 
forest mean 751 : -0.3855375 
forest RMSE 751 : 0.05433456 

nnet 751 : -0.3611556 
nnet mean 751 : -0.4066302 
nnet RMSE 751 : 0.1421707 


s: 752 
logit 752 : -0.4197955 
logit mean 752 : -0.4363761 
logit RMSE 752 : 0.06698808 

boosting 752 : -0.5609151 
boosting mean 752 : -0.4935134 
boosting RMSE 752 : 0.1470444 

forest 752 : -0.3865627 
forest mean 752 : -0.3855389 
forest RMSE 752 : 0.05430063 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 752 : -0.1450543 
nnet mean 752 : -0.4062824 
nnet RMSE 752 : 0.1423800 


s: 753 
logit 753 : -0.3412253 
logit mean 753 : -0.4362498 
logit RMSE 753 : 0.06697784 

boosting 753 : -0.6206916 
boosting mean 753 : -0.4936822 
boosting RMSE 753 : 0.1471667 

forest 753 : -0.4040508 
forest mean 753 : -0.3855634 
forest RMSE 753 : 0.05426476 

nnet 753 : -0.336294 
nnet mean 753 : -0.4061894 
nnet RMSE 753 : 0.1423044 


s: 754 
logit 754 : -0.3901509 
logit mean 754 : -0.4361886 
logit RMSE 754 : 0.06693438 

boosting 754 : -0.4474941 
boosting mean 754 : -0.493621 
boosting RMSE 754 : 0.1470792 

forest 754 : -0.4936178 
forest mean 754 : -0.3857068 
forest RMSE 754 : 0.05433584 

nnet 754 : -0.2885529 
nnet mean 754 : -0.4060334 
nnet RMSE 754 : 0.1422679 


s: 755 
logit 755 : -0.4118015 
logit mean 755 : -0.4361563 
logit RMSE 755 : 0.06689141 

boosting 755 : -0.6418672 
boosting mean 755 : -0.4938173 
boosting RMSE 755 : 0.1472451 

forest 755 : -0.3443655 
forest mean 755 : -0.385652 
forest RMSE 755 : 0.05433758 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 755 : -0.1332206 
nnet mean 755 : -0.4056721 
nnet RMSE 755 : 0.1425048 


s: 756 
logit 756 : -0.4451631 
logit mean 756 : -0.4361683 
logit RMSE 756 : 0.06686733 

boosting 756 : -0.6704519 
boosting mean 756 : -0.494051 
boosting RMSE 756 : 0.1474761 

forest 756 : -0.4421174 
forest mean 756 : -0.3857267 
forest RMSE 756 : 0.05432323 

nnet 756 : -0.8822645 
nnet mean 756 : -0.4063025 
nnet RMSE 756 : 0.1434866 


s: 757 
logit 757 : -0.4669175 
logit mean 757 : -0.4362089 
logit RMSE 757 : 0.0668674 

boosting 757 : -0.6509651 
boosting mean 757 : -0.4942583 
boosting RMSE 757 : 0.1476607 

forest 757 : -0.3490061 
forest mean 757 : -0.3856782 
forest RMSE 757 : 0.05431896 

nnet 757 : -0.3777234 
nnet mean 757 : -0.4062647 
nnet RMSE 757 : 0.1433941 


s: 758 
logit 758 : -0.4811714 
logit mean 758 : -0.4362682 
logit RMSE 758 : 0.06688829 

boosting 758 : -0.3481325 
boosting mean 758 : -0.4940655 
boosting RMSE 758 : 0.1475753 

forest 758 : -0.3667853 
forest mean 758 : -0.3856533 
forest RMSE 758 : 0.05429653 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 758 : -0.1784585 
nnet mean 758 : -0.4059642 
nnet RMSE 758 : 0.1435252 


s: 759 
logit 759 : -0.3882694 
logit mean 759 : -0.436205 
logit RMSE 759 : 0.06684557 

boosting 759 : -0.4874527 
boosting mean 759 : -0.4940568 
boosting RMSE 759 : 0.1475122 

forest 759 : -0.3907017 
forest mean 759 : -0.3856599 
forest RMSE 759 : 0.0542618 

nnet 759 : -0.4025252 
nnet mean 759 : -0.4059597 
nnet RMSE 759 : 0.1434306 


s: 760 
logit 760 : -0.486258 
logit mean 760 : -0.4362708 
logit RMSE 760 : 0.06687481 

boosting 760 : -0.5229252 
boosting mean 760 : -0.4940948 
boosting RMSE 760 : 0.1474825 

forest 760 : -0.4522087 
forest mean 760 : -0.3857475 
forest RMSE 760 : 0.05425914 

nnet 760 : -0.4747727 
nnet mean 760 : -0.4060502 
nnet RMSE 760 : 0.1433619 


s: 761 
logit 761 : -0.4228335 
logit mean 761 : -0.4362532 
logit RMSE 761 : 0.06683598 

boosting 761 : -0.5026022 
boosting mean 761 : -0.4941059 
boosting RMSE 761 : 0.1474325 

forest 761 : -0.3872763 
forest mean 761 : -0.3857495 
forest RMSE 761 : 0.05422544 

nnet 761 : -0.4585391 
nnet mean 761 : -0.4061192 
nnet RMSE 761 : 0.1432834 


s: 762 
logit 762 : -0.3734423 
logit mean 762 : -0.4361707 
logit RMSE 762 : 0.06679904 

boosting 762 : -0.5048345 
boosting mean 762 : -0.49412 
boosting RMSE 762 : 0.1473847 

forest 762 : -0.4473922 
forest mean 762 : -0.3858304 
forest RMSE 762 : 0.05421704 

nnet 762 : -0.2282432 
nnet mean 762 : -0.4058858 
nnet RMSE 762 : 0.1433245 


s: 763 
logit 763 : -0.4698099 
logit mean 763 : -0.4362148 
logit RMSE 763 : 0.06680308 

boosting 763 : -0.6989465 
boosting mean 763 : -0.4943885 
boosting RMSE 763 : 0.1476851 

forest 763 : -0.4449044 
forest mean 763 : -0.3859078 
forest RMSE 763 : 0.05420588 

nnet 763 : -0.6768691 
nnet mean 763 : -0.4062409 
nnet RMSE 763 : 0.1435808 


s: 764 
logit 764 : -0.3684666 
logit mean 764 : -0.4361261 
logit RMSE 764 : 0.06676909 

boosting 764 : -0.2924327 
boosting mean 764 : -0.4941241 
boosting RMSE 764 : 0.1476397 

forest 764 : -0.3137828 
forest mean 764 : -0.3858134 
forest RMSE 764 : 0.05426013 

nnet 764 : -0.4234126 
nnet mean 764 : -0.4062634 
nnet RMSE 764 : 0.1434893 


s: 765 
logit 765 : -0.4187681 
logit mean 765 : -0.4361035 
logit RMSE 765 : 0.06672889 

boosting 765 : -0.5387666 
boosting mean 765 : -0.4941825 
boosting RMSE 765 : 0.1476285 

forest 765 : -0.3315431 
forest mean 765 : -0.3857425 
forest RMSE 765 : 0.05428111 

nnet 765 : -0.444655 
nnet mean 765 : -0.4063136 
nnet RMSE 765 : 0.1434046 


s: 766 
logit 766 : -0.3597327 
logit mean 766 : -0.4360038 
logit RMSE 766 : 0.06670118 

boosting 766 : -0.702573 
boosting mean 766 : -0.4944545 
boosting RMSE 766 : 0.1479366 

forest 766 : -0.3872873 
forest mean 766 : -0.3857445 
forest RMSE 766 : 0.05424761 

nnet 766 : -0.5027817 
nnet mean 766 : -0.4064395 
nnet RMSE 766 : 0.1433591 


s: 767 
logit 767 : -0.4487935 
logit mean 767 : -0.4360204 
logit RMSE 767 : 0.06668097 

boosting 767 : -0.5683725 
boosting mean 767 : -0.4945509 
boosting RMSE 767 : 0.1479651 

forest 767 : -0.402838 
forest mean 767 : -0.3857668 
forest RMSE 767 : 0.05421233 

nnet 767 : -0.4530781 
nnet mean 767 : -0.4065003 
nnet RMSE 767 : 0.1432784 


s: 768 
logit 768 : -0.4229788 
logit mean 768 : -0.4360034 
logit RMSE 768 : 0.0666427 

boosting 768 : -0.4582557 
boosting mean 768 : -0.4945037 
boosting RMSE 768 : 0.1478837 

forest 768 : -0.3745202 
forest mean 768 : -0.3857521 
forest RMSE 768 : 0.05418483 

nnet 768 : -0.3979737 
nnet mean 768 : -0.4064892 
nnet RMSE 768 : 0.1431851 


s: 769 
logit 769 : -0.5096143 
logit mean 769 : -0.4360992 
logit RMSE 769 : 0.06671655 

boosting 769 : -0.5229783 
boosting mean 769 : -0.4945407 
boosting RMSE 769 : 0.147854 

forest 769 : -0.3872143 
forest mean 769 : -0.385754 
forest RMSE 769 : 0.05415155 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 769 : -0.2315623 
nnet mean 769 : -0.4062617 
nnet RMSE 769 : 0.1432208 


s: 770 
logit 770 : -0.3700411 
logit mean 770 : -0.4360134 
logit RMSE 770 : 0.06668196 

boosting 770 : -0.3201314 
boosting mean 770 : -0.4943142 
boosting RMSE 770 : 0.147786 

forest 770 : -0.4794797 
forest mean 770 : -0.3858757 
forest RMSE 770 : 0.05419212 

nnet 770 : -0.3116402 
nnet mean 770 : -0.4061389 
nnet RMSE 770 : 0.1431632 


s: 771 
logit 771 : -0.4805021 
logit mean 771 : -0.4360711 
logit RMSE 771 : 0.06670174 

boosting 771 : -0.4516165 
boosting mean 771 : -0.4942588 
boosting RMSE 771 : 0.1477018 

forest 771 : -0.3726355 
forest mean 771 : -0.3858586 
forest RMSE 771 : 0.05416593 

nnet 771 : -0.5771227 
nnet mean 771 : -0.4063606 
nnet RMSE 771 : 0.1432125 


s: 772 
logit 772 : -0.4598748 
logit mean 772 : -0.4361019 
logit RMSE 772 : 0.06669335 

boosting 772 : -0.4269651 
boosting mean 772 : -0.4941716 
boosting RMSE 772 : 0.1476093 

forest 772 : -0.4739513 
forest mean 772 : -0.3859727 
forest RMSE 772 : 0.05419623 

nnet 772 : -0.4196005 
nnet mean 772 : -0.4063778 
nnet RMSE 772 : 0.1431214 


s: 773 
logit 773 : -0.4952393 
logit mean 773 : -0.4361784 
logit RMSE 773 : 0.06673816 

boosting 773 : -0.5152735 
boosting mean 773 : -0.4941989 
boosting RMSE 773 : 0.1475721 

forest 773 : -0.3589076 
forest mean 773 : -0.3859377 
forest RMSE 773 : 0.05418133 

nnet 773 : -0.3061284 
nnet mean 773 : -0.4062481 
nnet RMSE 773 : 0.1430687 


s: 774 
logit 774 : -0.421758 
logit mean 774 : -0.4361598 
logit RMSE 774 : 0.06669962 

boosting 774 : -0.5220895 
boosting mean 774 : -0.494235 
boosting RMSE 774 : 0.1475420 

forest 774 : -0.4333123 
forest mean 774 : -0.3859989 
forest RMSE 774 : 0.05415955 

nnet 774 : -0.615565 
nnet mean 774 : -0.4065185 
nnet RMSE 774 : 0.143186 


s: 775 
logit 775 : -0.3968166 
logit mean 775 : -0.436109 
logit RMSE 775 : 0.06665667 

boosting 775 : -0.4384935 
boosting mean 775 : -0.494163 
boosting RMSE 775 : 0.1474532 

forest 775 : -0.3837983 
forest mean 775 : -0.385996 
forest RMSE 775 : 0.05412773 

nnet 775 : -0.5266774 
nnet mean 775 : -0.4066736 
nnet RMSE 775 : 0.1431659 


s: 776 
logit 776 : -0.4426847 
logit mean 776 : -0.4361175 
logit RMSE 776 : 0.06663133 

boosting 776 : -0.4524768 
boosting mean 776 : -0.4941093 
boosting RMSE 776 : 0.1473702 

forest 776 : -0.4131342 
forest mean 776 : -0.386031 
forest RMSE 776 : 0.0540949 

nnet 776 : -0.2998018 
nnet mean 776 : -0.4065358 
nnet RMSE 776 : 0.1431189 


s: 777 
logit 777 : -0.6121271 
logit mean 777 : -0.436344 
logit RMSE 777 : 0.06702188 

boosting 777 : -0.5907199 
boosting mean 777 : -0.4942337 
boosting RMSE 777 : 0.1474342 

forest 777 : -0.4360878 
forest mean 777 : -0.3860954 
forest RMSE 777 : 0.05407557 

nnet 777 : -0.4572774 
nnet mean 777 : -0.4066012 
nnet RMSE 777 : 0.1430415 


s: 778 
logit 778 : -0.4518408 
logit mean 778 : -0.4363639 
logit RMSE 778 : 0.06700458 

boosting 778 : -0.5131175 
boosting mean 778 : -0.4942579 
boosting RMSE 778 : 0.1473952 

forest 778 : -0.420517 
forest mean 778 : -0.3861397 
forest RMSE 778 : 0.05404582 

nnet 778 : -0.6273233 
nnet mean 778 : -0.4068849 
nnet RMSE 778 : 0.1431817 


s: 779 
logit 779 : -0.3809946 
logit mean 779 : -0.4362929 
logit RMSE 779 : 0.06696502 

boosting 779 : -0.6130701 
boosting mean 779 : -0.4944104 
boosting RMSE 779 : 0.1474983 

forest 779 : -0.3516749 
forest mean 779 : -0.3860954 
forest RMSE 779 : 0.05403886 

nnet 779 : -0.5219984 
nnet mean 779 : -0.4070326 
nnet RMSE 779 : 0.1431565 


s: 780 
logit 780 : -0.4415963 
logit mean 780 : -0.4362997 
logit RMSE 780 : 0.06693865 

boosting 780 : -0.4895927 
boosting mean 780 : -0.4944043 
boosting RMSE 780 : 0.1474386 

forest 780 : -0.3691588 
forest mean 780 : -0.3860737 
forest RMSE 780 : 0.0540155 

nnet 780 : -0.6668682 
nnet mean 780 : -0.4073657 
nnet RMSE 780 : 0.1433835 


s: 781 
logit 781 : -0.3751822 
logit mean 781 : -0.4362214 
logit RMSE 781 : 0.06690168 

boosting 781 : -0.3800173 
boosting mean 781 : -0.4942578 
boosting RMSE 781 : 0.1473459 

forest 781 : -0.4341583 
forest mean 781 : -0.3861353 
forest RMSE 781 : 0.05399474 

nnet 781 : -0.4578223 
nnet mean 781 : -0.4074304 
nnet RMSE 781 : 0.1433066 


s: 782 
logit 782 : -0.4539494 
logit mean 782 : -0.4362441 
logit RMSE 782 : 0.06688672 

boosting 782 : -0.6185428 
boosting mean 782 : -0.4944167 
boosting RMSE 782 : 0.1474589 

forest 782 : -0.3522948 
forest mean 782 : -0.386092 
forest RMSE 782 : 0.05398717 

nnet 782 : -0.4342939 
nnet mean 782 : -0.4074647 
nnet RMSE 782 : 0.1432202 


s: 783 
logit 783 : -0.4392134 
logit mean 783 : -0.4362479 
logit RMSE 783 : 0.06685868 

boosting 783 : -0.5313514 
boosting mean 783 : -0.4944639 
boosting RMSE 783 : 0.1474395 

forest 783 : -0.4503039 
forest mean 783 : -0.386174 
forest RMSE 783 : 0.05398262 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 783 : -0.2245614 
nnet mean 783 : -0.4072311 
nnet RMSE 783 : 0.1432659 


s: 784 
logit 784 : -0.4845684 
logit mean 784 : -0.4363095 
logit RMSE 784 : 0.06688426 

boosting 784 : -0.4556299 
boosting mean 784 : -0.4944144 
boosting RMSE 784 : 0.1473588 

forest 784 : -0.4010522 
forest mean 784 : -0.386193 
forest RMSE 784 : 0.0539482 

nnet 784 : -0.634674 
nnet mean 784 : -0.4075212 
nnet RMSE 784 : 0.1434196 


s: 785 
logit 785 : -0.4547026 
logit mean 785 : -0.4363329 
logit RMSE 785 : 0.06687015 

boosting 785 : -0.5607721 
boosting mean 785 : -0.4944989 
boosting RMSE 785 : 0.1473767 

forest 785 : -0.3587666 
forest mean 785 : -0.3861580 
forest RMSE 785 : 0.05393391 

nnet 785 : -0.4575773 
nnet mean 785 : -0.407585 
nnet RMSE 785 : 0.1433430 


s: 786 
logit 786 : -0.3764007 
logit mean 786 : -0.4362567 
logit RMSE 786 : 0.0668329 

boosting 786 : -0.253262 
boosting mean 786 : -0.494192 
boosting RMSE 786 : 0.1473759 

forest 786 : -0.3255490 
forest mean 786 : -0.3860809 
forest RMSE 786 : 0.05396497 

nnet 786 : -0.5901354 
nnet mean 786 : -0.4078172 
nnet RMSE 786 : 0.1434122 


s: 787 
logit 787 : -0.4708809 
logit mean 787 : -0.4363007 
logit RMSE 787 : 0.0668382 

boosting 787 : -0.4884261 
boosting mean 787 : -0.4941847 
boosting RMSE 787 : 0.1473159 

forest 787 : -0.4165307 
forest mean 787 : -0.3861196 
forest RMSE 787 : 0.05393389 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 787 : -0.2465644 
nnet mean 787 : -0.4076123 
nnet RMSE 787 : 0.1434254 


s: 788 
logit 788 : -0.450319 
logit mean 788 : -0.4363185 
logit RMSE 788 : 0.06681982 

boosting 788 : -0.7386189 
boosting mean 788 : -0.4944949 
boosting RMSE 788 : 0.1477158 

forest 788 : -0.3793291 
forest mean 788 : -0.386111 
forest RMSE 788 : 0.05390469 

nnet 788 : -0.1767454 
nnet mean 788 : -0.4073194 
nnet RMSE 788 : 0.1435548 


s: 789 
logit 789 : -0.4024122 
logit mean 789 : -0.4362755 
logit RMSE 789 : 0.06677752 

boosting 789 : -0.5441271 
boosting mean 789 : -0.4945578 
boosting RMSE 789 : 0.1477113 

forest 789 : -0.3578553 
forest mean 789 : -0.3860752 
forest RMSE 789 : 0.05389141 

nnet 789 : -0.6451667 
nnet mean 789 : -0.4076208 
nnet RMSE 789 : 0.1437291 


s: 790 
logit 790 : -0.3657727 
logit mean 790 : -0.4361863 
logit RMSE 790 : 0.06674635 

boosting 790 : -0.5923782 
boosting mean 790 : -0.4946816 
boosting RMSE 790 : 0.1477764 

forest 790 : -0.4117661 
forest mean 790 : -0.3861077 
forest RMSE 790 : 0.05385891 

nnet 790 : -0.6439126 
nnet mean 790 : -0.4079199 
nnet RMSE 790 : 0.1439 


s: 791 
logit 791 : -0.5091634 
logit mean 791 : -0.4362785 
logit RMSE 791 : 0.06681698 

boosting 791 : -0.1810621 
boosting mean 791 : -0.4942851 
boosting RMSE 791 : 0.1478880 

forest 791 : -0.3598079 
forest mean 791 : -0.3860745 
forest RMSE 791 : 0.05384383 

nnet 791 : -0.6441574 
nnet mean 791 : -0.4082186 
nnet RMSE 791 : 0.1440708 


s: 792 
logit 792 : -0.4231856 
logit mean 792 : -0.436262 
logit RMSE 792 : 0.06677986 

boosting 792 : -0.4939686 
boosting mean 792 : -0.4942847 
boosting RMSE 792 : 0.1478323 

forest 792 : -0.371616 
forest mean 792 : -0.3860562 
forest RMSE 792 : 0.05381927 

nnet 792 : -0.2176647 
nnet mean 792 : -0.407978 
nnet RMSE 792 : 0.1441255 


s: 793 
logit 793 : -0.4223483 
logit mean 793 : -0.4362444 
logit RMSE 793 : 0.06674246 

boosting 793 : -0.4718221 
boosting mean 793 : -0.4942564 
boosting RMSE 793 : 0.1477610 

forest 793 : -0.3132087 
forest mean 793 : -0.3859644 
forest RMSE 793 : 0.05387356 

nnet 793 : -0.5816955 
nnet mean 793 : -0.4081970 
nnet RMSE 793 : 0.1441791 


s: 794 
logit 794 : -0.4581215 
logit mean 794 : -0.436272 
logit RMSE 794 : 0.0667323 

boosting 794 : -0.4872155 
boosting mean 794 : -0.4942475 
boosting RMSE 794 : 0.1477004 

forest 794 : -0.3542032 
forest mean 794 : -0.3859243 
forest RMSE 794 : 0.05386415 

nnet 794 : -0.4705011 
nnet mean 794 : -0.4082755 
nnet RMSE 794 : 0.1441100 


s: 795 
logit 795 : -0.3297049 
logit mean 795 : -0.4361379 
logit RMSE 795 : 0.06673691 

boosting 795 : -0.6467767 
boosting mean 795 : -0.4944394 
boosting RMSE 795 : 0.1478667 

forest 795 : -0.2579237 
forest mean 795 : -0.3857633 
forest RMSE 795 : 0.05406559 

nnet 795 : -0.4586366 
nnet mean 795 : -0.4083389 
nnet RMSE 795 : 0.1440343 


s: 796 
logit 796 : -0.4519126 
logit mean 796 : -0.4361578 
logit RMSE 796 : 0.06672035 

boosting 796 : -0.4084169 
boosting mean 796 : -0.4943313 
boosting RMSE 796 : 0.1477741 

forest 796 : -0.2706579 
forest mean 796 : -0.3856187 
forest RMSE 796 : 0.05422576 

nnet 796 : -0.2933337 
nnet mean 796 : -0.4081944 
nnet RMSE 796 : 0.1439935 


s: 797 
logit 797 : -0.4869645 
logit mean 797 : -0.4362215 
logit RMSE 797 : 0.0667496 

boosting 797 : -0.6365891 
boosting mean 797 : -0.4945098 
boosting RMSE 797 : 0.1479190 

forest 797 : -0.5335828 
forest mean 797 : -0.3858044 
forest RMSE 797 : 0.05439791 

nnet 797 : -0.4198067 
nnet mean 797 : -0.4082089 
nnet RMSE 797 : 0.1439048 


s: 798 
logit 798 : -0.427366 
logit mean 798 : -0.4362104 
logit RMSE 798 : 0.0667148 

boosting 798 : -0.4643475 
boosting mean 798 : -0.494472 
boosting RMSE 798 : 0.1478438 

forest 798 : -0.3347681 
forest mean 798 : -0.3857404 
forest RMSE 798 : 0.05441284 

nnet 798 : -0.2958757 
nnet mean 798 : -0.4080682 
nnet RMSE 798 : 0.1438618 


s: 799 
logit 799 : -0.4453454 
logit mean 799 : -0.4362218 
logit RMSE 799 : 0.06669233 

boosting 799 : -0.4295938 
boosting mean 799 : -0.4943908 
boosting RMSE 799 : 0.1477550 

forest 799 : -0.3344948 
forest mean 799 : -0.3856763 
forest RMSE 799 : 0.05442813 

nnet 799 : -0.3901128 
nnet mean 799 : -0.4080457 
nnet RMSE 799 : 0.1437722 


s: 800 
logit 800 : -0.3780974 
logit mean 800 : -0.4361492 
logit RMSE 800 : 0.06665513 

boosting 800 : -0.3763924 
boosting mean 800 : -0.4942433 
boosting RMSE 800 : 0.1476650 

forest 800 : -0.309531 
forest mean 800 : -0.3855811 
forest RMSE 800 : 0.05448807 

nnet 800 : -0.5889807 
nnet mean 800 : -0.4082719 
nnet RMSE 800 : 0.1438376 


s: 801 
logit 801 : -0.5500405 
logit mean 801 : -0.4362914 
logit RMSE 801 : 0.06682414 

boosting 801 : -0.4892713 
boosting mean 801 : -0.4942371 
boosting RMSE 801 : 0.1476065 

forest 801 : -0.4142907 
forest mean 801 : -0.3856170 
forest RMSE 801 : 0.05445639 

nnet 801 : -0.5335497 
nnet mean 801 : -0.4084283 
nnet RMSE 801 : 0.1438252 


s: 802 
logit 802 : -0.469523 
logit mean 802 : -0.4363328 
logit RMSE 802 : 0.06682757 

boosting 802 : -0.5598263 
boosting mean 802 : -0.4943189 
boosting RMSE 802 : 0.1476223 

forest 802 : -0.3974087 
forest mean 802 : -0.3856317 
forest RMSE 802 : 0.0544225 

nnet 802 : -0.4784421 
nnet mean 802 : -0.4085156 
nnet RMSE 802 : 0.1437622 


s: 803 
logit 803 : -0.4430491 
logit mean 803 : -0.4363412 
logit RMSE 803 : 0.06680322 

boosting 803 : -0.7950742 
boosting mean 803 : -0.4946934 
boosting RMSE 803 : 0.1481877 

forest 803 : -0.3666581 
forest mean 803 : -0.385608 
forest RMSE 803 : 0.05440133 

nnet 803 : -0.3448431 
nnet mean 803 : -0.4084363 
nnet RMSE 803 : 0.1436858 


s: 804 
logit 804 : -0.5043239 
logit mean 804 : -0.4364257 
logit RMSE 804 : 0.06686297 

boosting 804 : -0.4104894 
boosting mean 804 : -0.4945887 
boosting RMSE 804 : 0.1480960 

forest 804 : -0.3956864 
forest mean 804 : -0.3856206 
forest RMSE 804 : 0.0543677 

nnet 804 : -0.5224927 
nnet mean 804 : -0.4085781 
nnet RMSE 804 : 0.1436614 


s: 805 
logit 805 : -0.4211816 
logit mean 805 : -0.4364068 
logit RMSE 805 : 0.0668256 

boosting 805 : -0.5670486 
boosting mean 805 : -0.4946787 
boosting RMSE 805 : 0.148121 

forest 805 : -0.3796454 
forest mean 805 : -0.3856131 
forest RMSE 805 : 0.05433866 

nnet 805 : -0.5423739 
nnet mean 805 : -0.4087444 
nnet RMSE 805 : 0.1436598 


s: 806 
logit 806 : -0.4586373 
logit mean 806 : -0.4364344 
logit RMSE 806 : 0.06681606 

boosting 806 : -0.6450143 
boosting mean 806 : -0.4948652 
boosting RMSE 806 : 0.1482805 

forest 806 : -0.4474673 
forest mean 806 : -0.3856899 
forest RMSE 806 : 0.05433067 

nnet 806 : -0.3040154 
nnet mean 806 : -0.4086144 
nnet RMSE 806 : 0.1436105 


s: 807 
logit 807 : -0.4659928 
logit mean 807 : -0.436471 
logit RMSE 807 : 0.06681504 

boosting 807 : -0.3687605 
boosting mean 807 : -0.494709 
boosting RMSE 807 : 0.1481926 

forest 807 : -0.3621565 
forest mean 807 : -0.3856607 
forest RMSE 807 : 0.05431334 

nnet 807 : -0.4697511 
nnet mean 807 : -0.4086902 
nnet RMSE 807 : 0.1435425 


s: 808 
logit 808 : -0.3294705 
logit mean 808 : -0.4363386 
logit RMSE 808 : 0.06681977 

boosting 808 : -0.5095803 
boosting mean 808 : -0.4947274 
boosting RMSE 808 : 0.1481511 

forest 808 : -0.3736334 
forest mean 808 : -0.3856458 
forest RMSE 808 : 0.05428764 

nnet 808 : -0.5495947 
nnet mean 808 : -0.4088646 
nnet RMSE 808 : 0.1435501 


s: 809 
logit 809 : -0.3974009 
logit mean 809 : -0.4362904 
logit RMSE 809 : 0.06677852 

boosting 809 : -0.3937324 
boosting mean 809 : -0.4946025 
boosting RMSE 809 : 0.1480596 

forest 809 : -0.320036 
forest mean 809 : -0.3855647 
forest RMSE 809 : 0.05432687 

nnet 809 : -0.516473 
nnet mean 809 : -0.4089976 
nnet RMSE 809 : 0.1435198 


s: 810 
logit 810 : -0.4794049 
logit mean 810 : -0.4363437 
logit RMSE 810 : 0.06679558 

boosting 810 : -0.452434 
boosting mean 810 : -0.4945505 
boosting RMSE 810 : 0.1479797 

forest 810 : -0.4306283 
forest mean 810 : -0.3856204 
forest RMSE 810 : 0.05430399 

nnet 810 : -0.4074724 
nnet mean 810 : -0.4089957 
nnet RMSE 810 : 0.1434314 


s: 811 
logit 811 : -0.4587170 
logit mean 811 : -0.4363713 
logit RMSE 811 : 0.06678622 

boosting 811 : -0.3559283 
boosting mean 811 : -0.4943795 
boosting RMSE 811 : 0.1478965 

forest 811 : -0.3885389 
forest mean 811 : -0.385624 
forest RMSE 811 : 0.05427199 

nnet 811 : -0.5504312 
nnet mean 811 : -0.4091701 
nnet RMSE 811 : 0.1434403 


s: 812 
logit 812 : -0.4776234 
logit mean 812 : -0.4364221 
logit RMSE 812 : 0.06680065 

boosting 812 : -0.4618751 
boosting mean 812 : -0.4943395 
boosting RMSE 812 : 0.1478214 

forest 812 : -0.3708523 
forest mean 812 : -0.3856058 
forest RMSE 812 : 0.05424821 

nnet 812 : -0.422677 
nnet mean 812 : -0.4091867 
nnet RMSE 812 : 0.1433541 


s: 813 
logit 813 : -0.4697659 
logit mean 813 : -0.4364631 
logit RMSE 813 : 0.06680438 

boosting 813 : -0.4291551 
boosting mean 813 : -0.4942593 
boosting RMSE 813 : 0.1477340 

forest 813 : -0.3499143 
forest mean 813 : -0.3855619 
forest RMSE 813 : 0.05424328 

nnet 813 : -0.1364562 
nnet mean 813 : -0.4088513 
nnet RMSE 813 : 0.1435638 


s: 814 
logit 814 : -0.4147472 
logit mean 814 : -0.4364364 
logit RMSE 814 : 0.06676533 

boosting 814 : -0.4354051 
boosting mean 814 : -0.494187 
boosting RMSE 814 : 0.1476484 

forest 814 : -0.3253061 
forest mean 814 : -0.3854879 
forest RMSE 814 : 0.05427314 

nnet 814 : -0.4459444 
nnet mean 814 : -0.4088968 
nnet RMSE 814 : 0.1434846 


s: 815 
logit 815 : -0.450084 
logit mean 815 : -0.4364531 
logit RMSE 815 : 0.06674742 

boosting 815 : -0.4721971 
boosting mean 815 : -0.49416 
boosting RMSE 815 : 0.1475795 

forest 815 : -0.3465082 
forest mean 815 : -0.38544 
forest RMSE 815 : 0.05427218 

nnet 815 : -0.2594566 
nnet mean 815 : -0.4087135 
nnet RMSE 815 : 0.1434810 


s: 816 
logit 816 : -0.4521158 
logit mean 816 : -0.4364723 
logit RMSE 816 : 0.06673145 

boosting 816 : -0.7620146 
boosting mean 816 : -0.4944883 
boosting RMSE 816 : 0.1480325 

forest 816 : -0.356803 
forest mean 816 : -0.3854049 
forest RMSE 816 : 0.05426 

nnet 816 : -0.6566418 
nnet mean 816 : -0.4090173 
nnet RMSE 816 : 0.1436743 


s: 817 
logit 817 : -0.3959923 
logit mean 817 : -0.4364228 
logit RMSE 817 : 0.06669074 

boosting 817 : -0.4858138 
boosting mean 817 : -0.4944777 
boosting RMSE 817 : 0.1479723 

forest 817 : -0.3933466 
forest mean 817 : -0.3854147 
forest RMSE 817 : 0.05422728 

nnet 817 : -0.2331103 
nnet mean 817 : -0.408802 
nnet RMSE 817 : 0.1437050 


s: 818 
logit 818 : -0.4303511 
logit mean 818 : -0.4364154 
logit RMSE 818 : 0.06665841 

boosting 818 : -0.4307784 
boosting mean 818 : -0.4943998 
boosting RMSE 818 : 0.1478858 

forest 818 : -0.3080215 
forest mean 818 : -0.3853200 
forest RMSE 818 : 0.05428946 

nnet 818 : -0.2294149 
nnet mean 818 : -0.4085827 
nnet RMSE 818 : 0.1437409 


s: 819 
logit 819 : -0.4519488 
logit mean 819 : -0.4364343 
logit RMSE 819 : 0.06664243 

boosting 819 : -0.3595882 
boosting mean 819 : -0.4942352 
boosting RMSE 819 : 0.1478022 

forest 819 : -0.3607303 
forest mean 819 : -0.38529 
forest RMSE 819 : 0.05427365 

nnet 819 : -0.3636754 
nnet mean 819 : -0.4085279 
nnet RMSE 819 : 0.1436587 


s: 820 
logit 820 : -0.3990936 
logit mean 820 : -0.4363888 
logit RMSE 820 : 0.06660179 

boosting 820 : -0.2393754 
boosting mean 820 : -0.4939244 
boosting RMSE 820 : 0.1478185 

forest 820 : -0.3475779 
forest mean 820 : -0.385244 
forest RMSE 820 : 0.05427143 

nnet 820 : -0.4451186 
nnet mean 820 : -0.4085725 
nnet RMSE 820 : 0.1435798 


s: 821 
logit 821 : -0.3778224 
logit mean 821 : -0.4363175 
logit RMSE 821 : 0.06656572 

boosting 821 : -0.1899631 
boosting mean 821 : -0.4935542 
boosting RMSE 821 : 0.1479102 

forest 821 : -0.4220108 
forest mean 821 : -0.3852888 
forest RMSE 821 : 0.05424381 

nnet 821 : -0.4107745 
nnet mean 821 : -0.4085752 
nnet RMSE 821 : 0.1434928 


s: 822 
logit 822 : -0.4031667 
logit mean 822 : -0.4362771 
logit RMSE 822 : 0.06652531 

boosting 822 : -0.4882233 
boosting mean 822 : -0.4935477 
boosting RMSE 822 : 0.1478522 

forest 822 : -0.4180232 
forest mean 822 : -0.3853286 
forest RMSE 822 : 0.05421445 

nnet 822 : -0.3590523 
nnet mean 822 : -0.4085149 
nnet RMSE 822 : 0.1434126 


s: 823 
logit 823 : -0.4957445 
logit mean 823 : -0.4363494 
logit RMSE 823 : 0.0665686 

boosting 823 : -0.6019818 
boosting mean 823 : -0.4936794 
boosting RMSE 823 : 0.1479300 

forest 823 : -0.3963854 
forest mean 823 : -0.3853421 
forest RMSE 823 : 0.05418165 

nnet 823 : -0.6819404 
nnet mean 823 : -0.4088471 
nnet RMSE 823 : 0.1436620 


s: 824 
logit 824 : -0.5003499 
logit mean 824 : -0.4364271 
logit RMSE 824 : 0.06661997 

boosting 824 : -0.6096391 
boosting mean 824 : -0.4938202 
boosting RMSE 824 : 0.1480205 

forest 824 : -0.3222575 
forest mean 824 : -0.3852655 
forest RMSE 824 : 0.05421645 

nnet 824 : -0.493937 
nnet mean 824 : -0.4089504 
nnet RMSE 824 : 0.1436121 


s: 825 
logit 825 : -0.4006829 
logit mean 825 : -0.4363837 
logit RMSE 825 : 0.06657959 

boosting 825 : -0.2775487 
boosting mean 825 : -0.493558 
boosting RMSE 825 : 0.1479922 

forest 825 : -0.2961944 
forest mean 825 : -0.3851575 
forest RMSE 825 : 0.05430397 

nnet 825 : -0.3203488 
nnet mean 825 : -0.408843 
nnet RMSE 825 : 0.1435518 


s: 826 
logit 826 : -0.4001239 
logit mean 826 : -0.4363398 
logit RMSE 826 : 0.06653928 

boosting 826 : -0.7051937 
boosting mean 826 : -0.4938142 
boosting RMSE 826 : 0.1482833 

forest 826 : -0.3620421 
forest mean 826 : -0.3851296 
forest RMSE 826 : 0.05428716 

nnet 826 : -0.4536001 
nnet mean 826 : -0.4088972 
nnet RMSE 826 : 0.143477 


s: 827 
logit 827 : -0.5030359 
logit mean 827 : -0.4364205 
logit RMSE 827 : 0.06659549 

boosting 827 : -0.5574399 
boosting mean 827 : -0.4938912 
boosting RMSE 827 : 0.1482947 

forest 827 : -0.4556921 
forest mean 827 : -0.3852149 
forest RMSE 827 : 0.05428888 

nnet 827 : -0.504174 
nnet mean 827 : -0.4090124 
nnet RMSE 827 : 0.1434360 


s: 828 
logit 828 : -0.4564954 
logit mean 828 : -0.4364447 
logit RMSE 828 : 0.06658421 

boosting 828 : -0.6335817 
boosting mean 828 : -0.4940599 
boosting RMSE 828 : 0.1484273 

forest 828 : -0.3872182 
forest mean 828 : -0.3852173 
forest RMSE 828 : 0.05425791 

nnet 828 : -0.2592719 
nnet mean 828 : -0.4088316 
nnet RMSE 828 : 0.1434327 


s: 829 
logit 829 : -0.4204841 
logit mean 829 : -0.4364255 
logit RMSE 829 : 0.06654784 

boosting 829 : -0.507754 
boosting mean 829 : -0.4940764 
boosting RMSE 829 : 0.1483849 

forest 829 : -0.3539898 
forest mean 829 : -0.3851796 
forest RMSE 829 : 0.05424871 

nnet 829 : -0.3944177 
nnet mean 829 : -0.4088142 
nnet RMSE 829 : 0.1433463 


s: 830 
logit 830 : -0.5221342 
logit mean 830 : -0.4365287 
logit RMSE 830 : 0.06664272 

boosting 830 : -0.5416295 
boosting mean 830 : -0.4941337 
boosting RMSE 830 : 0.1483770 

forest 830 : -0.3764994 
forest mean 830 : -0.3851692 
forest RMSE 830 : 0.05422216 

nnet 830 : -0.3834358 
nnet mean 830 : -0.4087836 
nnet RMSE 830 : 0.1432611 


s: 831 
logit 831 : -0.4622114 
logit mean 831 : -0.4365596 
logit RMSE 831 : 0.06663756 

boosting 831 : -0.6107262 
boosting mean 831 : -0.494274 
boosting RMSE 831 : 0.1484677 

forest 831 : -0.3924174 
forest mean 831 : -0.3851779 
forest RMSE 831 : 0.05419016 

nnet 831 : -0.6524599 
nnet mean 831 : -0.4090768 
nnet RMSE 831 : 0.1434425 


s: 832 
logit 832 : -0.4723335 
logit mean 832 : -0.4366026 
logit RMSE 832 : 0.0666447 

boosting 832 : -0.6616487 
boosting mean 832 : -0.4944752 
boosting RMSE 832 : 0.1486555 

forest 832 : -0.3279817 
forest mean 832 : -0.3851092 
forest RMSE 832 : 0.05421511 

nnet 832 : -0.2687444 
nnet mean 832 : -0.4089082 
nnet RMSE 832 : 0.1434284 


s: 833 
logit 833 : -0.4307137 
logit mean 833 : -0.4365956 
logit RMSE 833 : 0.06661319 

boosting 833 : -0.6844589 
boosting mean 833 : -0.4947032 
boosting RMSE 833 : 0.1488928 

forest 833 : -0.3952199 
forest mean 833 : -0.3851213 
forest RMSE 833 : 0.05418281 

nnet 833 : -0.2884200 
nnet mean 833 : -0.4087635 
nnet RMSE 833 : 0.1433945 


s: 834 
logit 834 : -0.3598087 
logit mean 834 : -0.4365035 
logit RMSE 834 : 0.06658778 

boosting 834 : -0.5718588 
boosting mean 834 : -0.4947957 
boosting RMSE 834 : 0.1489225 

forest 834 : -0.4120206 
forest mean 834 : -0.3851535 
forest RMSE 834 : 0.05415192 

nnet 834 : -0.4072069 
nnet mean 834 : -0.4087617 
nnet RMSE 834 : 0.1433087 


s: 835 
logit 835 : -0.4040341 
logit mean 835 : -0.4364646 
logit RMSE 835 : 0.06654805 

boosting 835 : -0.3510118 
boosting mean 835 : -0.4946235 
boosting RMSE 835 : 0.1488429 

forest 835 : -0.3065923 
forest mean 835 : -0.3850595 
forest RMSE 835 : 0.05421593 

nnet 835 : -0.2822840 
nnet mean 835 : -0.4086102 
nnet RMSE 835 : 0.1432808 


s: 836 
logit 836 : -0.4024473 
logit mean 836 : -0.4364239 
logit RMSE 836 : 0.06650829 

boosting 836 : -0.3194081 
boosting mean 836 : -0.494414 
boosting RMSE 836 : 0.14878 

forest 836 : -0.390088 
forest mean 836 : -0.3850655 
forest RMSE 836 : 0.05418458 

nnet 836 : -0.3720689 
nnet mean 836 : -0.4085665 
nnet RMSE 836 : 0.1431983 


s: 837 
logit 837 : -0.4348402 
logit mean 837 : -0.436422 
logit RMSE 837 : 0.06647945 

boosting 837 : -0.569573 
boosting mean 837 : -0.4945038 
boosting RMSE 837 : 0.1488066 

forest 837 : -0.3590099 
forest mean 837 : -0.3850343 
forest RMSE 837 : 0.05417074 

nnet 837 : -0.1335793 
nnet mean 837 : -0.4082379 
nnet RMSE 837 : 0.1434087 


s: 838 
logit 838 : -0.4285553 
logit mean 838 : -0.4364126 
logit RMSE 838 : 0.0664471 

boosting 838 : -0.3152127 
boosting mean 838 : -0.4942898 
boosting RMSE 838 : 0.1487466 

forest 838 : -0.3791454 
forest mean 838 : -0.3850273 
forest RMSE 838 : 0.0541432 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 838 : -0.2080336 
nnet mean 838 : -0.407999 
nnet RMSE 838 : 0.1434764 


s: 839 
logit 839 : -0.4327615 
logit mean 839 : -0.4364083 
logit RMSE 839 : 0.06641712 

boosting 839 : -0.4684962 
boosting mean 839 : -0.4942591 
boosting RMSE 839 : 0.1486767 

forest 839 : -0.3275122 
forest mean 839 : -0.3849588 
forest RMSE 839 : 0.05416876 

nnet 839 : -0.5003856 
nnet mean 839 : -0.4081091 
nnet RMSE 839 : 0.1434328 


s: 840 
logit 840 : -0.5338177 
logit mean 840 : -0.4365243 
logit RMSE 840 : 0.06653796 

boosting 840 : -0.530921 
boosting mean 840 : -0.4943027 
boosting RMSE 840 : 0.1486569 

forest 840 : -0.3547597 
forest mean 840 : -0.3849228 
forest RMSE 840 : 0.05415901 

nnet 840 : -0.7263915 
nnet mean 840 : -0.4084881 
nnet RMSE 840 : 0.1437891 


s: 841 
logit 841 : -0.419494 
logit mean 841 : -0.436504 
logit RMSE 841 : 0.06650179 

boosting 841 : -0.3394367 
boosting mean 841 : -0.4941186 
boosting RMSE 841 : 0.1485831 

forest 841 : -0.3807632 
forest mean 841 : -0.3849179 
forest RMSE 841 : 0.05413086 

nnet 841 : -0.5047878 
nnet mean 841 : -0.4086026 
nnet RMSE 841 : 0.1437490 


s: 842 
logit 842 : -0.4456608 
logit mean 842 : -0.4365149 
logit RMSE 842 : 0.06648091 

boosting 842 : -0.5607494 
boosting mean 842 : -0.4941977 
boosting RMSE 842 : 0.1485982 

forest 842 : -0.3534593 
forest mean 842 : -0.3848805 
forest RMSE 842 : 0.05412248 

nnet 842 : -0.3816657 
nnet mean 842 : -0.4085706 
nnet RMSE 842 : 0.1436650 


s: 843 
logit 843 : -0.4662207 
logit mean 843 : -0.4365501 
logit RMSE 843 : 0.0664806 

boosting 843 : -0.5776573 
boosting mean 843 : -0.4942967 
boosting RMSE 843 : 0.148636 

forest 843 : -0.4071649 
forest mean 843 : -0.3849069 
forest RMSE 843 : 0.05409093 

nnet 843 : -0.7256629 
nnet mean 843 : -0.4089467 
nnet RMSE 843 : 0.1440172 


s: 844 
logit 844 : -0.2628323 
logit mean 844 : -0.4363443 
logit RMSE 844 : 0.06660876 

boosting 844 : -0.3493475 
boosting mean 844 : -0.494125 
boosting RMSE 844 : 0.1485582 

forest 844 : -0.345599 
forest mean 844 : -0.3848604 
forest RMSE 844 : 0.0540913 

nnet 844 : -0.3748691 
nnet mean 844 : -0.4089063 
nnet RMSE 844 : 0.1439344 


s: 845 
logit 845 : -0.4204775 
logit mean 845 : -0.4363255 
logit RMSE 845 : 0.06657306 

boosting 845 : -0.4456325 
boosting mean 845 : -0.4940676 
boosting RMSE 845 : 0.1484785 

forest 845 : -0.262438 
forest mean 845 : -0.3847155 
forest RMSE 845 : 0.05426602 

nnet 845 : -0.3617854 
nnet mean 845 : -0.4088506 
nnet RMSE 845 : 0.1438553 


s: 846 
logit 846 : -0.4772192 
logit mean 846 : -0.4363739 
logit RMSE 846 : 0.06658665 

boosting 846 : -0.5996343 
boosting mean 846 : -0.4941924 
boosting RMSE 846 : 0.1485494 

forest 846 : -0.5024302 
forest mean 846 : -0.3848546 
forest RMSE 846 : 0.05434815 

nnet 846 : -0.5287103 
nnet mean 846 : -0.4089923 
nnet RMSE 846 : 0.1438383 


s: 847 
logit 847 : -0.4139866 
logit mean 847 : -0.4363474 
logit RMSE 847 : 0.06654906 

boosting 847 : -0.3825347 
boosting mean 847 : -0.4940605 
boosting RMSE 847 : 0.1484629 

forest 847 : -0.3305799 
forest mean 847 : -0.3847906 
forest RMSE 847 : 0.05436841 

nnet 847 : -0.1571229 
nnet mean 847 : -0.4086949 
nnet RMSE 847 : 0.1439954 


s: 848 
logit 848 : -0.4407879 
logit mean 848 : -0.4363527 
logit RMSE 848 : 0.06652456 

boosting 848 : -0.4358953 
boosting mean 848 : -0.4939919 
boosting RMSE 848 : 0.1483804 

forest 848 : -0.3230963 
forest mean 848 : -0.3847178 
forest RMSE 848 : 0.05440048 

nnet 848 : -0.1720175 
nnet mean 848 : -0.4084158 
nnet RMSE 848 : 0.1441233 


s: 849 
logit 849 : -0.3704404 
logit mean 849 : -0.436275 
logit RMSE 849 : 0.06649311 

boosting 849 : -0.645764 
boosting mean 849 : -0.4941707 
boosting RMSE 849 : 0.1485327 

forest 849 : -0.4453087 
forest mean 849 : -0.3847892 
forest RMSE 849 : 0.05439067 

nnet 849 : -0.3798724 
nnet mean 849 : -0.4083822 
nnet RMSE 849 : 0.1440400 


s: 850 
logit 850 : -0.5282917 
logit mean 850 : -0.4363833 
logit RMSE 850 : 0.06659952 

boosting 850 : -0.5195282 
boosting mean 850 : -0.4942005 
boosting RMSE 850 : 0.1485019 

forest 850 : -0.3754376 
forest mean 850 : -0.3847782 
forest RMSE 850 : 0.05436519 

nnet 850 : -0.2740097 
nnet mean 850 : -0.4082241 
nnet RMSE 850 : 0.1440201 


s: 851 
logit 851 : -0.3909988 
logit mean 851 : -0.4363299 
logit RMSE 851 : 0.06656109 

boosting 851 : -0.3008492 
boosting mean 851 : -0.4939733 
boosting RMSE 851 : 0.1484536 

forest 851 : -0.345163 
forest mean 851 : -0.3847316 
forest RMSE 851 : 0.05436575 

nnet 851 : -0.4146150 
nnet mean 851 : -0.4082316 
nnet RMSE 851 : 0.1439363 


s: 852 
logit 852 : -0.5199068 
logit mean 852 : -0.436428 
logit RMSE 852 : 0.06664873 

boosting 852 : -0.668425 
boosting mean 852 : -0.4941781 
boosting RMSE 852 : 0.1486511 

forest 852 : -0.4141851 
forest mean 852 : -0.3847662 
forest RMSE 852 : 0.05433601 

nnet 852 : -0.4695078 
nnet mean 852 : -0.4083035 
nnet RMSE 852 : 0.1438716 


s: 853 
logit 853 : -0.406686 
logit mean 853 : -0.4363932 
logit RMSE 853 : 0.06661005 

boosting 853 : -0.461297 
boosting mean 853 : -0.4941395 
boosting RMSE 853 : 0.1485788 

forest 853 : -0.4098208 
forest mean 853 : -0.3847956 
forest RMSE 853 : 0.05430519 

nnet 853 : -0.25267 
nnet mean 853 : -0.4081211 
nnet RMSE 853 : 0.1438757 


s: 854 
logit 854 : -0.4691041 
logit mean 854 : -0.4364315 
logit RMSE 854 : 0.06661302 

boosting 854 : -0.5069759 
boosting mean 854 : -0.4941546 
boosting RMSE 854 : 0.1485369 

forest 854 : -0.4126663 
forest mean 854 : -0.3848282 
forest RMSE 854 : 0.05427512 

nnet 854 : -0.3828671 
nnet mean 854 : -0.4080915 
nnet RMSE 854 : 0.1437926 


s: 855 
logit 855 : -0.4529017 
logit mean 855 : -0.4364507 
logit RMSE 855 : 0.06659864 

boosting 855 : -0.4990821 
boosting mean 855 : -0.4941603 
boosting RMSE 855 : 0.1484887 

forest 855 : -0.3397408 
forest mean 855 : -0.3847755 
forest RMSE 855 : 0.0542825 

nnet 855 : -0.7573148 
nnet mean 855 : -0.4084999 
nnet RMSE 855 : 0.1442271 


s: 856 
logit 856 : -0.542643 
logit mean 856 : -0.4365748 
logit RMSE 856 : 0.06673804 

boosting 856 : -0.2663731 
boosting mean 856 : -0.4938942 
boosting RMSE 856 : 0.1484722 

forest 856 : -0.4237825 
forest mean 856 : -0.384821 
forest RMSE 856 : 0.05425687 

nnet 856 : -0.3054077 
nnet mean 856 : -0.4083795 
nnet RMSE 856 : 0.1441791 


s: 857 
logit 857 : -0.4283986 
logit mean 857 : -0.4365653 
logit RMSE 857 : 0.06670615 

boosting 857 : -0.7271406 
boosting mean 857 : -0.4941664 
boosting RMSE 857 : 0.1488057 

forest 857 : -0.3575056 
forest mean 857 : -0.3847892 
forest RMSE 857 : 0.05424464 

nnet 857 : -0.4171124 
nnet mean 857 : -0.4083897 
nnet RMSE 857 : 0.1440961 


s: 858 
logit 858 : -0.4916626 
logit mean 858 : -0.4366295 
logit RMSE 858 : 0.06674067 

boosting 858 : -0.4983425 
boosting mean 858 : -0.4941713 
boosting RMSE 858 : 0.1487569 

forest 858 : -0.3442458 
forest mean 858 : -0.3847419 
forest RMSE 858 : 0.05424642 

nnet 858 : -0.3427075 
nnet mean 858 : -0.4083131 
nnet RMSE 858 : 0.1440254 


s: 859 
logit 859 : -0.4235926 
logit mean 859 : -0.4366143 
logit RMSE 859 : 0.06670667 

boosting 859 : -0.6637315 
boosting mean 859 : -0.4943686 
boosting RMSE 859 : 0.1489423 

forest 859 : -0.3954136 
forest mean 859 : -0.3847543 
forest RMSE 859 : 0.05421506 

nnet 859 : -0.5250241 
nnet mean 859 : -0.408449 
nnet RMSE 859 : 0.1440047 


s: 860 
logit 860 : -0.4335434 
logit mean 860 : -0.4366107 
logit RMSE 860 : 0.06667768 

boosting 860 : -0.6310573 
boosting mean 860 : -0.4945276 
boosting RMSE 860 : 0.1490641 

forest 860 : -0.3201899 
forest mean 860 : -0.3846792 
forest RMSE 860 : 0.05425184 

nnet 860 : -0.6913244 
nnet mean 860 : -0.4087779 
nnet RMSE 860 : 0.1442634 


s: 861 
logit 861 : -0.3902582 
logit mean 861 : -0.4365569 
logit RMSE 861 : 0.06663978 

boosting 861 : -0.4648659 
boosting mean 861 : -0.4944931 
boosting RMSE 861 : 0.1489939 

forest 861 : -0.3793487 
forest mean 861 : -0.3846731 
forest RMSE 861 : 0.05422489 

nnet 861 : -0.7560256 
nnet mean 861 : -0.4091812 
nnet RMSE 861 : 0.1446893 


s: 862 
logit 862 : -0.4807083 
logit mean 862 : -0.4366081 
logit RMSE 862 : 0.06665782 

boosting 862 : -0.4840197 
boosting mean 862 : -0.494481 
boosting RMSE 862 : 0.1489349 

forest 862 : -0.2454742 
forest mean 862 : -0.3845116 
forest RMSE 862 : 0.0544484 

nnet 862 : -0.2892883 
nnet mean 862 : -0.4090421 
nnet RMSE 862 : 0.1446545 


s: 863 
logit 863 : -0.3743433 
logit mean 863 : -0.436536 
logit RMSE 863 : 0.06662491 

boosting 863 : -0.5665054 
boosting mean 863 : -0.4945644 
boosting RMSE 863 : 0.1489565 

forest 863 : -0.4280208 
forest mean 863 : -0.384562 
forest RMSE 863 : 0.0544252 

nnet 863 : -0.3851138 
nnet mean 863 : -0.4090144 
nnet RMSE 863 : 0.1445715 


s: 864 
logit 864 : -0.4034634 
logit mean 864 : -0.4364977 
logit RMSE 864 : 0.06658645 

boosting 864 : -0.5689872 
boosting mean 864 : -0.4946506 
boosting RMSE 864 : 0.1489812 

forest 864 : -0.3958845 
forest mean 864 : -0.3845751 
forest RMSE 864 : 0.05439388 

nnet 864 : -0.6891741 
nnet mean 864 : -0.4093387 
nnet RMSE 864 : 0.1448224 


s: 865 
logit 865 : -0.3808395 
logit mean 865 : -0.4364333 
logit RMSE 865 : 0.06655114 

boosting 865 : -0.3977124 
boosting mean 865 : -0.4945385 
boosting RMSE 865 : 0.1488951 

forest 865 : -0.3757105 
forest mean 865 : -0.3845648 
forest RMSE 865 : 0.0543687 

nnet 865 : -0.3098436 
nnet mean 865 : -0.4092237 
nnet RMSE 865 : 0.1447711 


s: 866 
logit 866 : -0.5054278 
logit mean 866 : -0.436513 
logit RMSE 866 : 0.06660912 

boosting 866 : -0.4724102 
boosting mean 866 : -0.494513 
boosting RMSE 866 : 0.1488295 

forest 866 : -0.364429 
forest mean 866 : -0.3845416 
forest RMSE 866 : 0.05435075 

nnet 866 : -0.274597 
nnet mean 866 : -0.4090682 
nnet RMSE 866 : 0.1447502 


s: 867 
logit 867 : -0.4479344 
logit mean 867 : -0.4365262 
logit RMSE 867 : 0.0665906 

boosting 867 : -0.4402560 
boosting mean 867 : -0.4944504 
boosting RMSE 867 : 0.1487499 

forest 867 : -0.3227446 
forest mean 867 : -0.3844703 
forest RMSE 867 : 0.05438272 

nnet 867 : -0.4672678 
nnet mean 867 : -0.4091353 
nnet RMSE 867 : 0.1446848 


s: 868 
logit 868 : -0.4362469 
logit mean 868 : -0.4365259 
logit RMSE 868 : 0.0665636 

boosting 868 : -0.3166983 
boosting mean 868 : -0.4942456 
boosting RMSE 868 : 0.1486911 

forest 868 : -0.4048610 
forest mean 868 : -0.3844938 
forest RMSE 868 : 0.05435164 

nnet 868 : -0.4036485 
nnet mean 868 : -0.409129 
nnet RMSE 868 : 0.1446014 


s: 869 
logit 869 : -0.4636727 
logit mean 869 : -0.4365571 
logit RMSE 869 : 0.06656034 

boosting 869 : -0.6114465 
boosting mean 869 : -0.4943805 
boosting RMSE 869 : 0.1487785 

forest 869 : -0.4265923 
forest mean 869 : -0.3845423 
forest RMSE 869 : 0.05432784 

nnet 869 : -0.4755008 
nnet mean 869 : -0.4092054 
nnet RMSE 869 : 0.1445409 


s: 870 
logit 870 : -0.4788147 
logit mean 870 : -0.4366057 
logit RMSE 870 : 0.06657572 

boosting 870 : -0.4781405 
boosting mean 870 : -0.4943618 
boosting RMSE 870 : 0.1487166 

forest 870 : -0.3968567 
forest mean 870 : -0.3845564 
forest RMSE 870 : 0.05429672 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 870 : -0.1925796 
nnet mean 870 : -0.4089564 
nnet RMSE 870 : 0.1446289 


s: 871 
logit 871 : -0.4204049 
logit mean 871 : -0.4365871 
logit RMSE 871 : 0.06654109 

boosting 871 : -0.4084537 
boosting mean 871 : -0.4942632 
boosting RMSE 871 : 0.1486315 

forest 871 : -0.4277992 
forest mean 871 : -0.3846061 
forest RMSE 871 : 0.05427371 

nnet 871 : -0.6094454 
nnet mean 871 : -0.4091866 
nnet RMSE 871 : 0.1447199 


s: 872 
logit 872 : -0.3778683 
logit mean 872 : -0.4365197 
logit RMSE 872 : 0.06650714 

boosting 872 : -0.4464828 
boosting mean 872 : -0.4942084 
boosting RMSE 872 : 0.1485545 

forest 872 : -0.3931212 
forest mean 872 : -0.3846158 
forest RMSE 872 : 0.05424308 

nnet 872 : -0.3516597 
nnet mean 872 : -0.4091206 
nnet RMSE 872 : 0.1446462 


s: 873 
logit 873 : -0.4464919 
logit mean 873 : -0.4365312 
logit RMSE 873 : 0.06648766 

boosting 873 : -0.5303581 
boosting mean 873 : -0.4942498 
boosting RMSE 873 : 0.1485350 

forest 873 : -0.3182585 
forest mean 873 : -0.3845398 
forest RMSE 873 : 0.05428255 

nnet 873 : -0.4970018 
nnet mean 873 : -0.4092213 
nnet RMSE 873 : 0.1446006 


s: 874 
logit 874 : -0.5231273 
logit mean 874 : -0.4366302 
logit RMSE 874 : 0.06658001 

boosting 874 : -0.4919049 
boosting mean 874 : -0.4942471 
boosting RMSE 874 : 0.1484825 

forest 874 : -0.4147702 
forest mean 874 : -0.3845744 
forest RMSE 874 : 0.05425379 

nnet 874 : -0.3493933 
nnet mean 874 : -0.4091528 
nnet RMSE 874 : 0.144528 


s: 875 
logit 875 : -0.3713048 
logit mean 875 : -0.4365556 
logit RMSE 875 : 0.06654902 

boosting 875 : -0.4849512 
boosting mean 875 : -0.4942365 
boosting RMSE 875 : 0.1484254 

forest 875 : -0.3935058 
forest mean 875 : -0.3845846 
forest RMSE 875 : 0.05422322 

nnet 875 : -0.4496583 
nnet mean 875 : -0.4091991 
nnet RMSE 875 : 0.1444551 


s: 876 
logit 876 : -0.3257633 
logit mean 876 : -0.4364291 
logit RMSE 876 : 0.0665583 

boosting 876 : -0.3825676 
boosting mean 876 : -0.494109 
boosting RMSE 876 : 0.1483419 

forest 876 : -0.3400167 
forest mean 876 : -0.3845337 
forest RMSE 876 : 0.05423015 

nnet 876 : -0.4803083 
nnet mean 876 : -0.4092803 
nnet RMSE 876 : 0.1443982 


s: 877 
logit 877 : -0.4090774 
logit mean 877 : -0.4363979 
logit RMSE 877 : 0.06652105 

boosting 877 : -0.6219324 
boosting mean 877 : -0.4942548 
boosting RMSE 877 : 0.1484466 

forest 877 : -0.4074825 
forest mean 877 : -0.3845599 
forest RMSE 877 : 0.05419981 

nnet 877 : -0.4545146 
nnet mean 877 : -0.4093319 
nnet RMSE 877 : 0.1443276 


s: 878 
logit 878 : -0.534967 
logit mean 878 : -0.4365102 
logit RMSE 878 : 0.06663901 

boosting 878 : -0.390573 
boosting mean 878 : -0.4941367 
boosting RMSE 878 : 0.1483623 

forest 878 : -0.4426077 
forest mean 878 : -0.384626 
forest RMSE 878 : 0.05418802 

nnet 878 : -0.4282483 
nnet mean 878 : -0.4093534 
nnet RMSE 878 : 0.1442485 


s: 879 
logit 879 : -0.367572 
logit mean 879 : -0.4364318 
logit RMSE 879 : 0.06661008 

boosting 879 : -0.4166580 
boosting mean 879 : -0.4940485 
boosting RMSE 879 : 0.148279 

forest 879 : -0.3618408 
forest mean 879 : -0.3846001 
forest RMSE 879 : 0.05417248 

nnet 879 : -0.3915398 
nnet mean 879 : -0.4093331 
nnet RMSE 879 : 0.1441667 


s: 880 
logit 880 : -0.5168744 
logit mean 880 : -0.4365232 
logit RMSE 880 : 0.0666887 

boosting 880 : -0.5365011 
boosting mean 880 : -0.4940968 
boosting RMSE 880 : 0.1482661 

forest 880 : -0.3600286 
forest mean 880 : -0.3845722 
forest RMSE 880 : 0.05415845 

nnet 880 : -0.6113254 
nnet mean 880 : -0.4095627 
nnet RMSE 880 : 0.1442608 


s: 881 
logit 881 : -0.468583 
logit mean 881 : -0.4365596 
logit RMSE 881 : 0.06669088 

boosting 881 : -0.5185981 
boosting mean 881 : -0.4941246 
boosting RMSE 881 : 0.1482358 

forest 881 : -0.3342808 
forest mean 881 : -0.3845151 
forest RMSE 881 : 0.05417297 

nnet 881 : -0.3380884 
nnet mean 881 : -0.4094815 
nnet RMSE 881 : 0.1441940 


s: 882 
logit 882 : -0.5698856 
logit mean 882 : -0.4367107 
logit RMSE 882 : 0.06689808 

boosting 882 : -0.4749406 
boosting mean 882 : -0.4941028 
boosting RMSE 882 : 0.1481733 

forest 882 : -0.3439652 
forest mean 882 : -0.3844691 
forest RMSE 882 : 0.05417512 

nnet 882 : -0.4181624 
nnet mean 882 : -0.4094914 
nnet RMSE 882 : 0.1441135 


s: 883 
logit 883 : -0.3636275 
logit mean 883 : -0.4366279 
logit RMSE 883 : 0.06687139 

boosting 883 : -0.4075112 
boosting mean 883 : -0.4940048 
boosting RMSE 883 : 0.1480895 

forest 883 : -0.3324361 
forest mean 883 : -0.3844102 
forest RMSE 883 : 0.05419215 

nnet 883 : -0.11959 
nnet mean 883 : -0.4091631 
nnet RMSE 883 : 0.1443407 


s: 884 
logit 884 : -0.3878303 
logit mean 884 : -0.4365727 
logit RMSE 884 : 0.06683481 

boosting 884 : -0.5792148 
boosting mean 884 : -0.4941011 
boosting RMSE 884 : 0.1481284 

forest 884 : -0.375885 
forest mean 884 : -0.3844005 
forest RMSE 884 : 0.05416757 

nnet 884 : -0.3600398 
nnet mean 884 : -0.4091075 
nnet RMSE 884 : 0.1442652 


s: 885 
logit 885 : -0.3972348 
logit mean 885 : -0.4365283 
logit RMSE 885 : 0.0667971 

boosting 885 : -0.5676906 
boosting mean 885 : -0.4941843 
boosting RMSE 885 : 0.148152 

forest 885 : -0.3605749 
forest mean 885 : -0.3843736 
forest RMSE 885 : 0.05415317 

nnet 885 : -0.3622425 
nnet mean 885 : -0.4090545 
nnet RMSE 885 : 0.1441893 


s: 886 
logit 886 : -0.5255496 
logit mean 886 : -0.4366288 
logit RMSE 886 : 0.06689251 

boosting 886 : -0.5660771 
boosting mean 886 : -0.4942654 
boosting RMSE 886 : 0.1481735 

forest 886 : -0.4050823 
forest mean 886 : -0.384397 
forest RMSE 886 : 0.05412287 

nnet 886 : -0.4394937 
nnet mean 886 : -0.4090889 
nnet RMSE 886 : 0.1441140 


s: 887 
logit 887 : -0.3568133 
logit mean 887 : -0.4365388 
logit RMSE 887 : 0.06687052 

boosting 887 : -0.431963 
boosting mean 887 : -0.4941952 
boosting RMSE 887 : 0.1480938 

forest 887 : -0.3000602 
forest mean 887 : -0.3843019 
forest RMSE 887 : 0.05419634 

nnet 887 : -0.3576827 
nnet mean 887 : -0.4090309 
nnet RMSE 887 : 0.1440398 


s: 888 
logit 888 : -0.3974396 
logit mean 888 : -0.4364948 
logit RMSE 888 : 0.06683291 

boosting 888 : -0.4472241 
boosting mean 888 : -0.4941423 
boosting RMSE 888 : 0.1480189 

forest 888 : -0.3983216 
forest mean 888 : -0.3843177 
forest RMSE 888 : 0.05416585 

nnet 888 : -0.5758218 
nnet mean 888 : -0.4092188 
nnet RMSE 888 : 0.1440795 


s: 889 
logit 889 : -0.396855 
logit mean 889 : -0.4364502 
logit RMSE 889 : 0.0667954 

boosting 889 : -0.5668673 
boosting mean 889 : -0.4942241 
boosting RMSE 889 : 0.1480414 

forest 889 : -0.3724561 
forest mean 889 : -0.3843044 
forest RMSE 889 : 0.05414325 

nnet 889 : -0.5750733 
nnet mean 889 : -0.4094053 
nnet RMSE 889 : 0.1441181 


s: 890 
logit 890 : -0.4421895 
logit mean 890 : -0.4364566 
logit RMSE 890 : 0.06677283 

boosting 890 : -0.6344976 
boosting mean 890 : -0.4943817 
boosting RMSE 890 : 0.1481669 

forest 890 : -0.4083026 
forest mean 890 : -0.3843313 
forest RMSE 890 : 0.05411354 

nnet 890 : -0.5064788 
nnet mean 890 : -0.4095144 
nnet RMSE 890 : 0.1440813 


s: 891 
logit 891 : -0.2915709 
logit mean 891 : -0.436294 
logit RMSE 891 : 0.06683414 

boosting 891 : -0.4613687 
boosting mean 891 : -0.4943447 
boosting RMSE 891 : 0.1480980 

forest 891 : -0.3013280 
forest mean 891 : -0.3842382 
forest RMSE 891 : 0.0541841 

nnet 891 : -0.482595 
nnet mean 891 : -0.4095964 
nnet RMSE 891 : 0.1440270 


s: 892 
logit 892 : -0.4363516 
logit mean 892 : -0.4362941 
logit RMSE 892 : 0.06680776 

boosting 892 : -0.3953954 
boosting mean 892 : -0.4942337 
boosting RMSE 892 : 0.1480150 

forest 892 : -0.4155938 
forest mean 892 : -0.3842733 
forest RMSE 892 : 0.05415623 

nnet 892 : -0.5598821 
nnet mean 892 : -0.4097649 
nnet RMSE 892 : 0.1440458 


s: 893 
logit 893 : -0.4427157 
logit mean 893 : -0.4363013 
logit RMSE 893 : 0.06678564 

boosting 893 : -0.6623423 
boosting mean 893 : -0.494422 
boosting RMSE 893 : 0.1481924 

forest 893 : -0.3615658 
forest mean 893 : -0.3842479 
forest RMSE 893 : 0.05414118 

nnet 893 : -0.3103823 
nnet mean 893 : -0.4096536 
nnet RMSE 893 : 0.1439964 


s: 894 
logit 894 : -0.388933 
logit mean 894 : -0.4362483 
logit RMSE 894 : 0.0667493 

boosting 894 : -0.2400748 
boosting mean 894 : -0.4941375 
boosting RMSE 894 : 0.1482060 

forest 894 : -0.3901159 
forest mean 894 : -0.3842544 
forest RMSE 894 : 0.0541119 

nnet 894 : -0.5536289 
nnet mean 894 : -0.4098147 
nnet RMSE 894 : 0.1440075 


s: 895 
logit 895 : -0.3802222 
logit mean 895 : -0.4361857 
logit RMSE 895 : 0.06671528 

boosting 895 : -0.5316863 
boosting mean 895 : -0.4941794 
boosting RMSE 895 : 0.1481886 

forest 895 : -0.3137411 
forest mean 895 : -0.3841757 
forest RMSE 895 : 0.05415847 

nnet 895 : -0.203558 
nnet mean 895 : -0.4095842 
nnet RMSE 895 : 0.1440767 


s: 896 
logit 896 : -0.4969147 
logit mean 896 : -0.4362535 
logit RMSE 896 : 0.0667566 

boosting 896 : -0.5402727 
boosting mean 896 : -0.4942309 
boosting RMSE 896 : 0.14818 

forest 896 : -0.3688455 
forest mean 896 : -0.3841586 
forest RMSE 896 : 0.05413824 

nnet 896 : -0.6149226 
nnet mean 896 : -0.4098134 
nnet RMSE 896 : 0.1441752 


s: 897 
logit 897 : -0.451219 
logit mean 897 : -0.4362701 
logit RMSE 897 : 0.06674129 

boosting 897 : -0.504526 
boosting mean 897 : -0.4942424 
boosting RMSE 897 : 0.1481385 

forest 897 : -0.4000378 
forest mean 897 : -0.3841763 
forest RMSE 897 : 0.05410806 

nnet 897 : -0.4615431 
nnet mean 897 : -0.4098711 
nnet RMSE 897 : 0.1441095 


s: 898 
logit 898 : -0.3906669 
logit mean 898 : -0.4362194 
logit RMSE 898 : 0.06670485 

boosting 898 : -0.4278022 
boosting mean 898 : -0.4941684 
boosting RMSE 898 : 0.1480589 

forest 898 : -0.3680305 
forest mean 898 : -0.3841583 
forest RMSE 898 : 0.05408845 

nnet 898 : -0.6252666 
nnet mean 898 : -0.4101109 
nnet RMSE 898 : 0.1442252 


s: 899 
logit 899 : -0.395254 
logit mean 899 : -0.4361738 
logit RMSE 899 : 0.06666792 

boosting 899 : -0.532484 
boosting mean 899 : -0.494211 
boosting RMSE 899 : 0.1480425 

forest 899 : -0.4732855 
forest mean 899 : -0.3842574 
forest RMSE 899 : 0.05411358 

nnet 899 : -0.4980293 
nnet mean 899 : -0.4102087 
nnet RMSE 899 : 0.1441821 


s: 900 
logit 900 : -0.4984381 
logit mean 900 : -0.436243 
logit RMSE 900 : 0.06671162 

boosting 900 : -0.7177223 
boosting mean 900 : -0.4944593 
boosting RMSE 900 : 0.1483388 

forest 900 : -0.3235039 
forest mean 900 : -0.3841899 
forest RMSE 900 : 0.05414359 

nnet 900 : -0.3751722 
nnet mean 900 : -0.4101698 
nnet RMSE 900 : 0.1441043 


s: 901 
logit 901 : -0.4490772 
logit mean 901 : -0.4362572 
logit RMSE 901 : 0.06669463 

boosting 901 : -0.6485706 
boosting mean 901 : -0.4946304 
boosting RMSE 901 : 0.1484875 

forest 901 : -0.3647386 
forest mean 901 : -0.3841683 
forest RMSE 901 : 0.05412628 

nnet 901 : -0.5902037 
nnet mean 901 : -0.4103696 
nnet RMSE 901 : 0.1441637 


s: 902 
logit 902 : -0.4375496 
logit mean 902 : -0.4362587 
logit RMSE 902 : 0.06666938 

boosting 902 : -0.5879475 
boosting mean 902 : -0.4947338 
boosting RMSE 902 : 0.1485371 

forest 902 : -0.363871 
forest mean 902 : -0.3841458 
forest RMSE 902 : 0.05410964 

nnet 902 : -0.4183332 
nnet mean 902 : -0.4103784 
nnet RMSE 902 : 0.1440850 


s: 903 
logit 903 : -0.4060527 
logit mean 903 : -0.4362252 
logit RMSE 903 : 0.06663276 

boosting 903 : -0.4214907 
boosting mean 903 : -0.4946527 
boosting RMSE 903 : 0.1484565 

forest 903 : -0.3998449 
forest mean 903 : -0.3841632 
forest RMSE 903 : 0.05407967 

nnet 903 : -0.1839825 
nnet mean 903 : -0.4101277 
nnet RMSE 903 : 0.1441845 


s: 904 
logit 904 : -0.3611764 
logit mean 904 : -0.4361422 
logit RMSE 904 : 0.06660841 

boosting 904 : -0.4432497 
boosting mean 904 : -0.4945959 
boosting RMSE 904 : 0.1483814 

forest 904 : -0.4257237 
forest mean 904 : -0.3842092 
forest RMSE 904 : 0.05405653 

nnet 904 : -0.3421505 
nnet mean 904 : -0.4100525 
nnet RMSE 904 : 0.1441176 


s: 905 
logit 905 : -0.4472519 
logit mean 905 : -0.4361545 
logit RMSE 905 : 0.06659013 

boosting 905 : -0.7611197 
boosting mean 905 : -0.4948904 
boosting RMSE 905 : 0.1487844 

forest 905 : -0.3784267 
forest mean 905 : -0.3842028 
forest RMSE 905 : 0.05403141 

nnet 905 : -0.3431902 
nnet mean 905 : -0.4099786 
nnet RMSE 905 : 0.1440503 


s: 906 
logit 906 : -0.5414152 
logit mean 906 : -0.4362706 
logit RMSE 906 : 0.06671899 

boosting 906 : -0.4062982 
boosting mean 906 : -0.4947926 
boosting RMSE 906 : 0.1487024 

forest 906 : -0.4876265 
forest mean 906 : -0.3843169 
forest RMSE 906 : 0.05408 

nnet 906 : -0.658519 
nnet mean 906 : -0.410253 
nnet RMSE 906 : 0.1442268 


s: 907 
logit 907 : -0.3126918 
logit mean 907 : -0.4361344 
logit RMSE 907 : 0.06674519 

boosting 907 : -0.4791488 
boosting mean 907 : -0.4947753 
boosting RMSE 907 : 0.1486437 

forest 907 : -0.4247096 
forest mean 907 : -0.3843615 
forest RMSE 907 : 0.0540564 

nnet 907 : -0.4048493 
nnet mean 907 : -0.410247 
nnet RMSE 907 : 0.1441473 


s: 908 
logit 908 : -0.35501 
logit mean 908 : -0.4360450 
logit RMSE 908 : 0.06672513 

boosting 908 : -0.4417842 
boosting mean 908 : -0.494717 
boosting RMSE 908 : 0.1485682 

forest 908 : -0.4074932 
forest mean 908 : -0.3843870 
forest RMSE 908 : 0.0540272 

nnet 908 : -0.411601 
nnet mean 908 : -0.4102485 
nnet RMSE 908 : 0.1440685 


s: 909 
logit 909 : -0.4831337 
logit mean 909 : -0.4360968 
logit RMSE 909 : 0.0667454 

boosting 909 : -0.5638309 
boosting mean 909 : -0.494793 
boosting RMSE 909 : 0.1485859 

forest 909 : -0.4029742 
forest mean 909 : -0.3844074 
forest RMSE 909 : 0.05399757 

nnet 909 : -0.2847793 
nnet mean 909 : -0.4101105 
nnet RMSE 909 : 0.1440399 


s: 910 
logit 910 : -0.4343705 
logit mean 910 : -0.4360950 
logit RMSE 910 : 0.06671844 

boosting 910 : -0.4846346 
boosting mean 910 : -0.4947819 
boosting RMSE 910 : 0.1485307 

forest 910 : -0.3580673 
forest mean 910 : -0.3843785 
forest RMSE 910 : 0.05398579 

nnet 910 : -0.3470131 
nnet mean 910 : -0.4100411 
nnet RMSE 910 : 0.1439714 


s: 911 
logit 911 : -0.4035529 
logit mean 911 : -0.4360592 
logit RMSE 911 : 0.06668192 

boosting 911 : -0.352898 
boosting mean 911 : -0.4946261 
boosting RMSE 911 : 0.1484574 

forest 911 : -0.4486659 
forest mean 911 : -0.384449 
forest RMSE 911 : 0.05398023 

nnet 911 : -0.2031346 
nnet mean 911 : -0.409814 
nnet RMSE 911 : 0.1440402 


s: 912 
logit 912 : -0.4180667 
logit mean 912 : -0.4360395 
logit RMSE 912 : 0.06664804 

boosting 912 : -0.5866654 
boosting mean 912 : -0.494727 
boosting RMSE 912 : 0.1485047 

forest 912 : -0.36533 
forest mean 912 : -0.3844281 
forest RMSE 912 : 0.05396285 

nnet 912 : -0.3573699 
nnet mean 912 : -0.4097565 
nnet RMSE 912 : 0.1439681 


s: 913 
logit 913 : -0.4305783 
logit mean 913 : -0.4360335 
logit RMSE 913 : 0.06661921 

boosting 913 : -0.3003964 
boosting mean 913 : -0.4945142 
boosting RMSE 913 : 0.1484599 

forest 913 : -0.3931531 
forest mean 913 : -0.3844376 
forest RMSE 913 : 0.05393376 

nnet 913 : -0.3493015 
nnet mean 913 : -0.4096903 
nnet RMSE 913 : 0.143899 


s: 914 
logit 914 : -0.4796626 
logit mean 914 : -0.4360813 
logit RMSE 914 : 0.06663488 

boosting 914 : -0.4556282 
boosting mean 914 : -0.4944716 
boosting RMSE 914 : 0.1483901 

forest 914 : -0.3899959 
forest mean 914 : -0.3844437 
forest RMSE 914 : 0.05390526 

nnet 914 : -0.4557869 
nnet mean 914 : -0.4097407 
nnet RMSE 914 : 0.1438321 


s: 915 
logit 915 : -0.3239716 
logit mean 915 : -0.4359587 
logit RMSE 915 : 0.06664587 

boosting 915 : -0.3006379 
boosting mean 915 : -0.4942598 
boosting RMSE 915 : 0.1483454 

forest 915 : -0.3223283 
forest mean 915 : -0.3843758 
forest RMSE 915 : 0.05393696 

nnet 915 : -0.4190416 
nnet mean 915 : -0.4097509 
nnet RMSE 915 : 0.1437549 


s: 916 
logit 916 : -0.5028664 
logit mean 916 : -0.4360318 
logit RMSE 916 : 0.06669614 

boosting 916 : -0.5697918 
boosting mean 916 : -0.4943423 
boosting RMSE 916 : 0.1483705 

forest 916 : -0.4174564 
forest mean 916 : -0.3844119 
forest RMSE 916 : 0.05391059 

nnet 916 : -0.1686501 
nnet mean 916 : -0.4094877 
nnet RMSE 916 : 0.1438796 


s: 917 
logit 917 : -0.4612555 
logit mean 917 : -0.4360593 
logit RMSE 917 : 0.06669045 

boosting 917 : -0.4777771 
boosting mean 917 : -0.4943242 
boosting RMSE 917 : 0.1483118 

forest 917 : -0.3844777 
forest mean 917 : -0.384412 
forest RMSE 917 : 0.05388363 

nnet 917 : -0.5369958 
nnet mean 917 : -0.4096267 
nnet RMSE 917 : 0.1438722 


s: 918 
logit 918 : -0.392451 
logit mean 918 : -0.4360118 
logit RMSE 918 : 0.06665458 

boosting 918 : -0.5255573 
boosting mean 918 : -0.4943582 
boosting RMSE 918 : 0.1482889 

forest 918 : -0.4148158 
forest mean 918 : -0.3844451 
forest RMSE 918 : 0.05385649 

nnet 918 : -0.2649353 
nnet mean 918 : -0.4094691 
nnet RMSE 918 : 0.1438629 


s: 919 
logit 919 : -0.4499955 
logit mean 919 : -0.436027 
logit RMSE 919 : 0.06663871 

boosting 919 : -0.4137527 
boosting mean 919 : -0.4942705 
boosting RMSE 919 : 0.1482089 

forest 919 : -0.4223092 
forest mean 919 : -0.3844863 
forest RMSE 919 : 0.05383221 

nnet 919 : -0.4661323 
nnet mean 919 : -0.4095308 
nnet RMSE 919 : 0.1438012 


s: 920 
logit 920 : -0.442888 
logit mean 920 : -0.4360345 
logit RMSE 920 : 0.0666175 

boosting 920 : -0.6075361 
boosting mean 920 : -0.4943936 
boosting RMSE 920 : 0.1482863 

forest 920 : -0.4466433 
forest mean 920 : -0.3845539 
forest RMSE 920 : 0.05382492 

nnet 920 : -0.5792567 
nnet mean 920 : -0.4097153 
nnet RMSE 920 : 0.1438445 


s: 921 
logit 921 : -0.5191635 
logit mean 921 : -0.4361247 
logit RMSE 921 : 0.066697 

boosting 921 : -0.3840484 
boosting mean 921 : -0.4942738 
boosting RMSE 921 : 0.1482067 

forest 921 : -0.4019456 
forest mean 921 : -0.3845728 
forest RMSE 921 : 0.05379573 

nnet 921 : -0.3623341 
nnet mean 921 : -0.4096638 
nnet RMSE 921 : 0.1437717 


s: 922 
logit 922 : -0.4926207 
logit mean 922 : -0.436186 
logit RMSE 922 : 0.06673057 

boosting 922 : -0.611899 
boosting mean 922 : -0.4944014 
boosting RMSE 922 : 0.1482906 

forest 922 : -0.3724581 
forest mean 922 : -0.3845596 
forest RMSE 922 : 0.0537742 

nnet 922 : -0.3674502 
nnet mean 922 : -0.409618 
nnet RMSE 922 : 0.1436977 


s: 923 
logit 923 : -0.4799344 
logit mean 923 : -0.4362334 
logit RMSE 923 : 0.06674629 

boosting 923 : -0.4304464 
boosting mean 923 : -0.4943321 
boosting RMSE 923 : 0.1482136 

forest 923 : -0.3234305 
forest mean 923 : -0.3844934 
forest RMSE 923 : 0.05380412 

nnet 923 : -0.601172 
nnet mean 923 : -0.4098256 
nnet RMSE 923 : 0.1437724 


s: 924 
logit 924 : -0.5723101 
logit mean 924 : -0.4363807 
logit RMSE 924 : 0.06695057 

boosting 924 : -0.4395216 
boosting mean 924 : -0.4942728 
boosting RMSE 924 : 0.1481391 

forest 924 : -0.4317416 
forest mean 924 : -0.3845445 
forest RMSE 924 : 0.05378513 

nnet 924 : -0.2689306 
nnet mean 924 : -0.4096731 
nnet RMSE 924 : 0.1437593 


s: 925 
logit 925 : -0.4359551 
logit mean 925 : -0.4363802 
logit RMSE 925 : 0.06692481 

boosting 925 : -0.5833266 
boosting mean 925 : -0.494369 
boosting RMSE 925 : 0.1481816 

forest 925 : -0.457211 
forest mean 925 : -0.3846231 
forest RMSE 925 : 0.05378896 

nnet 925 : -0.3664035 
nnet mean 925 : -0.4096263 
nnet RMSE 925 : 0.1436858 


s: 926 
logit 926 : -0.487262 
logit mean 926 : -0.4364351 
logit RMSE 926 : 0.06695011 

boosting 926 : -0.3945936 
boosting mean 926 : -0.4942613 
boosting RMSE 926 : 0.1481017 

forest 926 : -0.4152692 
forest mean 926 : -0.3846562 
forest RMSE 926 : 0.05376225 

nnet 926 : -0.3403734 
nnet mean 926 : -0.4095515 
nnet RMSE 926 : 0.1436216 


s: 927 
logit 927 : -0.4022680 
logit mean 927 : -0.4363983 
logit RMSE 927 : 0.06691403 

boosting 927 : -0.2297899 
boosting mean 927 : -0.493976 
boosting RMSE 927 : 0.1481273 

forest 927 : -0.355914 
forest mean 927 : -0.3846252 
forest RMSE 927 : 0.05375275 

nnet 927 : -0.3154234 
nnet mean 927 : -0.40945 
nnet RMSE 927 : 0.1435710 


s: 928 
logit 928 : -0.3936746 
logit mean 928 : -0.4363522 
logit RMSE 928 : 0.06687829 

boosting 928 : -0.6207614 
boosting mean 928 : -0.4941126 
boosting RMSE 928 : 0.1482248 

forest 928 : -0.3992754 
forest mean 928 : -0.384641 
forest RMSE 928 : 0.05372378 

nnet 928 : -0.2467517 
nnet mean 928 : -0.4092746 
nnet RMSE 928 : 0.1435817 


s: 929 
logit 929 : -0.3088115 
logit mean 929 : -0.436215 
logit RMSE 929 : 0.0669092 

boosting 929 : -0.3539299 
boosting mean 929 : -0.4939617 
boosting RMSE 929 : 0.1481527 

forest 929 : -0.3588347 
forest mean 929 : -0.3846132 
forest RMSE 929 : 0.05371184 

nnet 929 : -0.3135964 
nnet mean 929 : -0.4091717 
nnet RMSE 929 : 0.1435324 


s: 930 
logit 930 : -0.4204778 
logit mean 930 : -0.436198 
logit RMSE 930 : 0.0668766 

boosting 930 : -0.2931531 
boosting mean 930 : -0.4937458 
boosting RMSE 930 : 0.1481145 

forest 930 : -0.3854127 
forest mean 930 : -0.3846140 
forest RMSE 930 : 0.05368509 

nnet 930 : -0.3799469 
nnet mean 930 : -0.4091402 
nnet RMSE 930 : 0.1434568 


s: 931 
logit 931 : -0.4693959 
logit mean 931 : -0.4362337 
logit RMSE 931 : 0.06687935 

boosting 931 : -0.589982 
boosting mean 931 : -0.4938492 
boosting RMSE 931 : 0.1481658 

forest 931 : -0.421169 
forest mean 931 : -0.3846533 
forest RMSE 931 : 0.05366073 

nnet 931 : -0.2226419 
nnet mean 931 : -0.4089399 
nnet RMSE 931 : 0.1434975 


s: 932 
logit 932 : -0.3162449 
logit mean 932 : -0.4361050 
logit RMSE 932 : 0.06689974 

boosting 932 : -0.36736 
boosting mean 932 : -0.4937135 
boosting RMSE 932 : 0.1480901 

forest 932 : -0.3328886 
forest mean 932 : -0.3845978 
forest RMSE 932 : 0.05367697 

nnet 932 : -0.3415219 
nnet mean 932 : -0.4088676 
nnet RMSE 932 : 0.1434333 


s: 933 
logit 933 : -0.3948196 
logit mean 933 : -0.4360607 
logit RMSE 933 : 0.0668641 

boosting 933 : -0.5206543 
boosting mean 933 : -0.4937423 
boosting RMSE 933 : 0.1480634 

forest 933 : -0.4259051 
forest mean 933 : -0.3846420 
forest RMSE 933 : 0.0536549 

nnet 933 : -0.487457 
nnet mean 933 : -0.4089518 
nnet RMSE 933 : 0.1433850 


s: 934 
logit 934 : -0.4213125 
logit mean 934 : -0.4360449 
logit RMSE 934 : 0.06683193 

boosting 934 : -0.4506905 
boosting mean 934 : -0.4936962 
boosting RMSE 934 : 0.1479934 

forest 934 : -0.4213115 
forest mean 934 : -0.3846813 
forest RMSE 934 : 0.0536307 

nnet 934 : -0.5686141 
nnet mean 934 : -0.4091227 
nnet RMSE 934 : 0.1434143 


s: 935 
logit 935 : -0.3976457 
logit mean 935 : -0.4360038 
logit RMSE 935 : 0.06679622 

boosting 935 : -0.3942729 
boosting mean 935 : -0.4935899 
boosting RMSE 935 : 0.1479144 

forest 935 : -0.3740921 
forest mean 935 : -0.38467 
forest RMSE 935 : 0.05360871 

nnet 935 : -0.4602111 
nnet mean 935 : -0.4091774 
nnet RMSE 935 : 0.1433512 


s: 936 
logit 936 : -0.4409879 
logit mean 936 : -0.4360092 
logit RMSE 936 : 0.06677397 

boosting 936 : -0.6315043 
boosting mean 936 : -0.4937372 
boosting RMSE 936 : 0.1480289 

forest 936 : -0.4011626 
forest mean 936 : -0.3846876 
forest RMSE 936 : 0.05358008 

nnet 936 : -0.6019878 
nnet mean 936 : -0.4093834 
nnet RMSE 936 : 0.1434266 


s: 937 
logit 937 : -0.3805992 
logit mean 937 : -0.43595 
logit RMSE 937 : 0.06674134 

boosting 937 : -0.4504718 
boosting mean 937 : -0.4936911 
boosting RMSE 937 : 0.1479591 

forest 937 : -0.3702926 
forest mean 937 : -0.3846722 
forest RMSE 937 : 0.05356028 

nnet 937 : -0.3631609 
nnet mean 937 : -0.4093341 
nnet RMSE 937 : 0.1433551 


s: 938 
logit 938 : -0.4157697 
logit mean 938 : -0.4359285 
logit RMSE 938 : 0.06670774 

boosting 938 : -0.3520828 
boosting mean 938 : -0.4935401 
boosting RMSE 938 : 0.1478885 

forest 938 : -0.4206615 
forest mean 938 : -0.3847106 
forest RMSE 938 : 0.05353597 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 938 : -0.1911174 
nnet mean 938 : -0.4091014 
nnet RMSE 938 : 0.1434409 


s: 939 
logit 939 : -0.4677111 
logit mean 939 : -0.4359624 
logit RMSE 939 : 0.06670882 

boosting 939 : -0.544838 
boosting mean 939 : -0.4935947 
boosting RMSE 939 : 0.1478852 

forest 939 : -0.4771875 
forest mean 939 : -0.3848091 
forest RMSE 939 : 0.05356671 

nnet 939 : -0.6956733 
nnet mean 939 : -0.4094066 
nnet RMSE 939 : 0.1436888 


s: 940 
logit 940 : -0.5007271 
logit mean 940 : -0.4360313 
logit RMSE 940 : 0.06675422 

boosting 940 : -0.3823258 
boosting mean 940 : -0.4934764 
boosting RMSE 940 : 0.1478077 

forest 940 : -0.4272663 
forest mean 940 : -0.3848543 
forest RMSE 940 : 0.0535456 

nnet 940 : -0.665618 
nnet mean 940 : -0.4096792 
nnet RMSE 940 : 0.1438735 


s: 941 
logit 941 : -0.4044454 
logit mean 941 : -0.4359977 
logit RMSE 941 : 0.0667189 

boosting 941 : -0.5094092 
boosting mean 941 : -0.4934933 
boosting RMSE 941 : 0.1477722 

forest 941 : -0.4376215 
forest mean 941 : -0.3849103 
forest RMSE 941 : 0.05353119 

nnet 941 : -0.5371777 
nnet mean 941 : -0.4098147 
nnet RMSE 941 : 0.1438665 


s: 942 
logit 942 : -0.3537737 
logit mean 942 : -0.4359104 
logit RMSE 942 : 0.06670048 

boosting 942 : -0.3905465 
boosting mean 942 : -0.493384 
boosting RMSE 942 : 0.1476940 

forest 942 : -0.3166026 
forest mean 942 : -0.3848378 
forest RMSE 942 : 0.05357172 

nnet 942 : -0.5705937 
nnet mean 942 : -0.4099853 
nnet RMSE 942 : 0.1438975 


s: 943 
logit 943 : -0.5635767 
logit mean 943 : -0.4360458 
logit RMSE 943 : 0.06687758 

boosting 943 : -0.6803464 
boosting mean 943 : -0.4935823 
boosting RMSE 943 : 0.1478977 

forest 943 : -0.3780012 
forest mean 943 : -0.3848306 
forest RMSE 943 : 0.0535481 

nnet 943 : -0.4396634 
nnet mean 943 : -0.4100168 
nnet RMSE 943 : 0.143827 


s: 944 
logit 944 : -0.4708423 
logit mean 944 : -0.4360827 
logit RMSE 944 : 0.06688191 

boosting 944 : -0.5279658 
boosting mean 944 : -0.4936187 
boosting RMSE 944 : 0.1478780 

forest 944 : -0.3623026 
forest mean 944 : -0.3848067 
forest RMSE 944 : 0.0535338 

nnet 944 : -0.5588092 
nnet mean 944 : -0.4101744 
nnet RMSE 944 : 0.1438437 


s: 945 
logit 945 : -0.3751174 
logit mean 945 : -0.4360181 
logit RMSE 945 : 0.06685141 

boosting 945 : -0.4672079 
boosting mean 945 : -0.4935907 
boosting RMSE 945 : 0.1478160 

forest 945 : -0.2750908 
forest mean 945 : -0.3846906 
forest RMSE 945 : 0.05365953 

nnet 945 : -0.5133508 
nnet mean 945 : -0.4102836 
nnet RMSE 945 : 0.1438148 


s: 946 
logit 946 : -0.4286891 
logit mean 946 : -0.4360104 
logit RMSE 946 : 0.06682258 

boosting 946 : -0.4571123 
boosting mean 946 : -0.4935522 
boosting RMSE 946 : 0.1477495 

forest 946 : -0.3814987 
forest mean 946 : -0.3846872 
forest RMSE 946 : 0.05363453 

nnet 946 : -0.3444127 
nnet mean 946 : -0.410214 
nnet RMSE 946 : 0.1437502 


s: 947 
logit 947 : -0.3833398 
logit mean 947 : -0.4359548 
logit RMSE 947 : 0.06678948 

boosting 947 : -0.4445662 
boosting mean 947 : -0.4935005 
boosting RMSE 947 : 0.1476785 

forest 947 : -0.3751511 
forest mean 947 : -0.3846772 
forest RMSE 947 : 0.05361229 

nnet 947 : -0.4400713 
nnet mean 947 : -0.4102455 
nnet RMSE 947 : 0.1436801 


s: 948 
logit 948 : -0.4305762 
logit mean 948 : -0.4359491 
logit RMSE 948 : 0.06676163 

boosting 948 : -0.3387417 
boosting mean 948 : -0.4933372 
boosting RMSE 948 : 0.1476140 

forest 948 : -0.3476183 
forest mean 948 : -0.3846381 
forest RMSE 948 : 0.05361101 

nnet 948 : -0.3535174 
nnet mean 948 : -0.4101857 
nnet RMSE 948 : 0.1436123 


s: 949 
logit 949 : -0.4845261 
logit mean 949 : -0.4360003 
logit RMSE 949 : 0.06678284 

boosting 949 : -0.402776 
boosting mean 949 : -0.4932418 
boosting RMSE 949 : 0.1475363 

forest 949 : -0.3422459 
forest mean 949 : -0.3845934 
forest RMSE 949 : 0.05361554 

nnet 949 : -0.4259334 
nnet mean 949 : -0.4102023 
nnet RMSE 949 : 0.1435391 


s: 950 
logit 950 : -0.3691805 
logit mean 950 : -0.4359300 
logit RMSE 950 : 0.06675517 

boosting 950 : -0.3985713 
boosting mean 950 : -0.4931421 
boosting RMSE 950 : 0.1474586 

forest 950 : -0.3693196 
forest mean 950 : -0.3845773 
forest RMSE 950 : 0.05359656 

nnet 950 : -0.3666843 
nnet mean 950 : -0.4101565 
nnet RMSE 950 : 0.1434676 


s: 951 
logit 951 : -0.4712795 
logit mean 951 : -0.4359671 
logit RMSE 951 : 0.06676009 

boosting 951 : -0.5178768 
boosting mean 951 : -0.4931681 
boosting RMSE 951 : 0.1474306 

forest 951 : -0.4445481 
forest mean 951 : -0.3846404 
forest RMSE 951 : 0.05358785 

nnet 951 : -0.2803161 
nnet mean 951 : -0.4100199 
nnet RMSE 951 : 0.1434446 


s: 952 
logit 952 : -0.4210006 
logit mean 952 : -0.4359514 
logit RMSE 952 : 0.06672849 

boosting 952 : -0.4296789 
boosting mean 952 : -0.4931014 
boosting RMSE 952 : 0.1473563 

forest 952 : -0.3711686 
forest mean 952 : -0.3846262 
forest RMSE 952 : 0.05356784 

nnet 952 : -0.3621864 
nnet mean 952 : -0.4099697 
nnet RMSE 952 : 0.1433745 


s: 953 
logit 953 : -0.3825388 
logit mean 953 : -0.4358954 
logit RMSE 953 : 0.06669587 

boosting 953 : -0.4175031 
boosting mean 953 : -0.4930221 
boosting RMSE 953 : 0.1472801 

forest 953 : -0.3549914 
forest mean 953 : -0.3845951 
forest RMSE 953 : 0.05355958 

nnet 953 : -0.0959256 
nnet mean 953 : -0.4096401 
nnet RMSE 953 : 0.1436374 


s: 954 
logit 954 : -0.4091304 
logit mean 954 : -0.4358673 
logit RMSE 954 : 0.06666156 

boosting 954 : -0.4353077 
boosting mean 954 : -0.4929616 
boosting RMSE 954 : 0.1472073 

forest 954 : -0.3096565 
forest mean 954 : -0.3845166 
forest RMSE 954 : 0.05361135 

nnet 954 : -0.4357588 
nnet mean 954 : -0.4096675 
nnet RMSE 954 : 0.1435668 


s: 955 
logit 955 : -0.5087818 
logit mean 955 : -0.4359436 
logit RMSE 955 : 0.06671957 

boosting 955 : -0.6208903 
boosting mean 955 : -0.4930956 
boosting RMSE 955 : 0.1473037 

forest 955 : -0.4161896 
forest mean 955 : -0.3845497 
forest RMSE 955 : 0.05358584 

nnet 955 : -0.5163999 
nnet mean 955 : -0.4097793 
nnet RMSE 955 : 0.143541 


s: 956 
logit 956 : -0.4854641 
logit mean 956 : -0.4359954 
logit RMSE 956 : 0.06674193 

boosting 956 : -0.6968332 
boosting mean 956 : -0.4933087 
boosting RMSE 956 : 0.1475393 

forest 956 : -0.3275199 
forest mean 956 : -0.3844901 
forest RMSE 956 : 0.05360908 

nnet 956 : -0.4623309 
nnet mean 956 : -0.4098343 
nnet RMSE 956 : 0.1434801 


s: 957 
logit 957 : -0.4511804 
logit mean 957 : -0.4360113 
logit RMSE 957 : 0.06672756 

boosting 957 : -0.4083657 
boosting mean 957 : -0.4932199 
boosting RMSE 957 : 0.1474625 

forest 957 : -0.3838132 
forest mean 957 : -0.3844894 
forest RMSE 957 : 0.05358362 

nnet 957 : -0.4157423 
nnet mean 957 : -0.4098404 
nnet RMSE 957 : 0.143406 


s: 958 
logit 958 : -0.3792021 
logit mean 958 : -0.435952 
logit RMSE 958 : 0.06669611 

boosting 958 : -0.2977145 
boosting mean 958 : -0.4930159 
boosting RMSE 958 : 0.1474225 

forest 958 : -0.3895808 
forest mean 958 : -0.3844947 
forest RMSE 958 : 0.0535567 

nnet 958 : -0.2512989 
nnet mean 958 : -0.4096749 
nnet RMSE 958 : 0.1434116 


s: 959 
logit 959 : -0.4580093 
logit mean 959 : -0.435975 
logit RMSE 959 : 0.06668764 

boosting 959 : -0.6533389 
boosting mean 959 : -0.493183 
boosting RMSE 959 : 0.1475726 

forest 959 : -0.3514185 
forest mean 959 : -0.3844602 
forest RMSE 959 : 0.05355176 

nnet 959 : -0.5818324 
nnet mean 959 : -0.4098545 
nnet RMSE 959 : 0.1434570 


s: 960 
logit 960 : -0.4395376 
logit mean 960 : -0.4359787 
logit RMSE 960 : 0.06666512 

boosting 960 : -0.4858101 
boosting mean 960 : -0.4931754 
boosting RMSE 960 : 0.1475217 

forest 960 : -0.3700402 
forest mean 960 : -0.3844452 
forest RMSE 960 : 0.05353259 

nnet 960 : -0.5536892 
nnet mean 960 : -0.4100043 
nnet RMSE 960 : 0.1434681 


s: 961 
logit 961 : -0.3837921 
logit mean 961 : -0.4359244 
logit RMSE 961 : 0.06663247 

boosting 961 : -0.445632 
boosting mean 961 : -0.4931259 
boosting RMSE 961 : 0.1474523 

forest 961 : -0.4021059 
forest mean 961 : -0.3844636 
forest RMSE 961 : 0.05350477 

nnet 961 : -0.4710247 
nnet mean 961 : -0.4100678 
nnet RMSE 961 : 0.1434117 


s: 962 
logit 962 : -0.3501442 
logit mean 962 : -0.4358353 
logit RMSE 962 : 0.06661723 

boosting 962 : -0.2886824 
boosting mean 962 : -0.4929134 
boosting RMSE 962 : 0.1474193 

forest 962 : -0.2928576 
forest mean 962 : -0.3843683 
forest RMSE 962 : 0.05358841 

nnet 962 : -0.5228883 
nnet mean 962 : -0.4101851 
nnet RMSE 962 : 0.1433919 


s: 963 
logit 963 : -0.43163 
logit mean 963 : -0.4358309 
logit RMSE 963 : 0.06659043 

boosting 963 : -0.725286 
boosting mean 963 : -0.4931547 
boosting RMSE 963 : 0.1477151 

forest 963 : -0.3789234 
forest mean 963 : -0.3843627 
forest RMSE 963 : 0.05356489 

nnet 963 : -0.4722568 
nnet mean 963 : -0.4102495 
nnet RMSE 963 : 0.1433364 


s: 964 
logit 964 : -0.4574801 
logit mean 964 : -0.4358533 
logit RMSE 964 : 0.06658163 

boosting 964 : -0.5995024 
boosting mean 964 : -0.493265 
boosting RMSE 964 : 0.1477783 

forest 964 : -0.4252748 
forest mean 964 : -0.3844051 
forest RMSE 964 : 0.05354329 

nnet 964 : -0.5450076 
nnet mean 964 : -0.4103893 
nnet RMSE 964 : 0.1433381 


s: 965 
logit 965 : -0.3502027 
logit mean 965 : -0.4357646 
logit RMSE 965 : 0.06656642 

boosting 965 : -0.415264 
boosting mean 965 : -0.4931842 
boosting RMSE 965 : 0.1477025 

forest 965 : -0.3952295 
forest mean 965 : -0.3844163 
forest RMSE 965 : 0.05351576 

nnet 965 : -0.4608409 
nnet mean 965 : -0.4104416 
nnet RMSE 965 : 0.1432772 


s: 966 
logit 966 : -0.4797982 
logit mean 966 : -0.4358102 
logit RMSE 966 : 0.06658148 

boosting 966 : -0.5742807 
boosting mean 966 : -0.4932681 
boosting RMSE 966 : 0.1477325 

forest 966 : -0.4003597 
forest mean 966 : -0.3844328 
forest RMSE 966 : 0.05348805 

nnet 966 : -0.500949 
nnet mean 966 : -0.4105353 
nnet RMSE 966 : 0.1432399 


s: 967 
logit 967 : -0.5821137 
logit mean 967 : -0.4359615 
logit RMSE 967 : 0.06680424 

boosting 967 : -0.3443436 
boosting mean 967 : -0.4931141 
boosting RMSE 967 : 0.1476669 

forest 967 : -0.3512443 
forest mean 967 : -0.3843985 
forest RMSE 967 : 0.05348337 

nnet 967 : -0.4598204 
nnet mean 967 : -0.4105862 
nnet RMSE 967 : 0.1431787 


s: 968 
logit 968 : -0.4603327 
logit mean 968 : -0.4359866 
logit RMSE 968 : 0.06679788 

boosting 968 : -0.3508676 
boosting mean 968 : -0.4929671 
boosting RMSE 968 : 0.1475991 

forest 968 : -0.3808689 
forest mean 968 : -0.3843949 
forest RMSE 968 : 0.05345928 

nnet 968 : -0.3421439 
nnet mean 968 : -0.4105155 
nnet RMSE 968 : 0.1431168 


s: 969 
logit 969 : -0.5251017 
logit mean 969 : -0.4360786 
logit RMSE 969 : 0.06688425 

boosting 969 : -0.4002794 
boosting mean 969 : -0.4928715 
boosting RMSE 969 : 0.1475229 

forest 969 : -0.4618494 
forest mean 969 : -0.3844748 
forest RMSE 969 : 0.05346861 

nnet 969 : -0.3335034 
nnet mean 969 : -0.4104361 
nnet RMSE 969 : 0.1430589 


s: 970 
logit 970 : -0.4817746 
logit mean 970 : -0.4361257 
logit RMSE 970 : 0.06690131 

boosting 970 : -0.5922783 
boosting mean 970 : -0.492974 
boosting RMSE 970 : 0.1475760 

forest 970 : -0.4096032 
forest mean 970 : -0.3845007 
forest RMSE 970 : 0.05344194 

nnet 970 : -0.5517006 
nnet mean 970 : -0.4105817 
nnet RMSE 970 : 0.1430681 


s: 971 
logit 971 : -0.3904244 
logit mean 971 : -0.4360787 
logit RMSE 971 : 0.06686756 

boosting 971 : -0.3733859 
boosting mean 971 : -0.4928508 
boosting RMSE 971 : 0.1475025 

forest 971 : -0.4416919 
forest mean 971 : -0.3845596 
forest RMSE 971 : 0.05343116 

nnet 971 : -0.8567159 
nnet mean 971 : -0.4110412 
nnet RMSE 971 : 0.1437436 


s: 972 
logit 972 : -0.4364525 
logit mean 972 : -0.436079 
logit RMSE 972 : 0.06684338 

boosting 972 : -0.6554006 
boosting mean 972 : -0.493018 
boosting RMSE 972 : 0.1476540 

forest 972 : -0.3588627 
forest mean 972 : -0.3845332 
forest RMSE 972 : 0.05341997 

nnet 972 : -0.3153548 
nnet mean 972 : -0.4109427 
nnet RMSE 972 : 0.1436952 


s: 973 
logit 973 : -0.4919357 
logit mean 973 : -0.4361364 
logit RMSE 973 : 0.066874 

boosting 973 : -0.5557661 
boosting mean 973 : -0.4930825 
boosting RMSE 973 : 0.1476626 

forest 973 : -0.3955129 
forest mean 973 : -0.3845445 
forest RMSE 973 : 0.05339271 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 973 : -0.2397414 
nnet mean 973 : -0.4107668 
nnet RMSE 973 : 0.1437132 


s: 974 
logit 974 : -0.4397301 
logit mean 974 : -0.4361401 
logit RMSE 974 : 0.06685178 

boosting 974 : -0.5050136 
boosting mean 974 : -0.4930948 
boosting RMSE 974 : 0.1476251 

forest 974 : -0.2600291 
forest mean 974 : -0.3844166 
forest RMSE 974 : 0.05355342 

nnet 974 : -0.6163603 
nnet mean 974 : -0.4109778 
nnet RMSE 974 : 0.1438067 


s: 975 
logit 975 : -0.4127014 
logit mean 975 : -0.4361161 
logit RMSE 975 : 0.06681873 

boosting 975 : -0.4606354 
boosting mean 975 : -0.4930615 
boosting RMSE 975 : 0.1475622 

forest 975 : -0.3901621 
forest mean 975 : -0.3844225 
forest RMSE 975 : 0.05352688 

nnet 975 : -0.4895012 
nnet mean 975 : -0.4110584 
nnet RMSE 975 : 0.1437615 


s: 976 
logit 976 : -0.472714 
logit mean 976 : -0.4361536 
logit RMSE 976 : 0.06682503 

boosting 976 : -0.5423577 
boosting mean 976 : -0.493112 
boosting RMSE 976 : 0.1475569 

forest 976 : -0.4050422 
forest mean 976 : -0.3844436 
forest RMSE 976 : 0.05349969 

nnet 976 : -0.2009066 
nnet mean 976 : -0.4108431 
nnet RMSE 976 : 0.1438291 


s: 977 
logit 977 : -0.3021769 
logit mean 977 : -0.4360165 
logit RMSE 977 : 0.06686411 

boosting 977 : -0.4588667 
boosting mean 977 : -0.493077 
boosting RMSE 977 : 0.1474934 

forest 977 : -0.3433234 
forest mean 977 : -0.3844016 
forest RMSE 977 : 0.05350304 

nnet 977 : -0.3833467 
nnet mean 977 : -0.4108149 
nnet RMSE 977 : 0.1437564 


s: 978 
logit 978 : -0.307018 
logit mean 978 : -0.4358846 
logit RMSE 978 : 0.06689602 

boosting 978 : -0.3820146 
boosting mean 978 : -0.4929634 
boosting RMSE 978 : 0.1474191 

forest 978 : -0.3449394 
forest mean 978 : -0.3843612 
forest RMSE 978 : 0.05350466 

nnet 978 : -0.2551522 
nnet mean 978 : -0.4106558 
nnet RMSE 978 : 0.1437575 


s: 979 
logit 979 : -0.3510847 
logit mean 979 : -0.4357979 
logit RMSE 979 : 0.06688012 

boosting 979 : -0.4631804 
boosting mean 979 : -0.492933 
boosting RMSE 979 : 0.1473576 

forest 979 : -0.340754 
forest mean 979 : -0.3843167 
forest RMSE 979 : 0.05351084 

nnet 979 : -0.3888184 
nnet mean 979 : -0.4106334 
nnet RMSE 979 : 0.1436845 


s: 980 
logit 980 : -0.4163109 
logit mean 980 : -0.4357781 
logit RMSE 980 : 0.06684802 

boosting 980 : -0.3344408 
boosting mean 980 : -0.4927712 
boosting RMSE 980 : 0.1472973 

forest 980 : -0.3635803 
forest mean 980 : -0.3842955 
forest RMSE 980 : 0.05349618 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 980 : -0.3100784 
nnet mean 980 : -0.4105308 
nnet RMSE 980 : 0.1436399 


s: 981 
logit 981 : -0.4461848 
logit mean 981 : -0.4357887 
logit RMSE 981 : 0.06683021 

boosting 981 : -0.5441689 
boosting mean 981 : -0.4928236 
boosting RMSE 981 : 0.1472942 

forest 981 : -0.4165221 
forest mean 981 : -0.3843284 
forest RMSE 981 : 0.05347151 

nnet 981 : -0.2850726 
nnet mean 981 : -0.4104030 
nnet RMSE 981 : 0.1436136 


s: 982 
logit 982 : -0.479057 
logit mean 982 : -0.4358327 
logit RMSE 982 : 0.0668438 

boosting 982 : -0.5512316 
boosting mean 982 : -0.4928831 
boosting RMSE 982 : 0.1472982 

forest 982 : -0.3749943 
forest mean 982 : -0.3843188 
forest RMSE 982 : 0.05345023 

nnet 982 : -0.4696584 
nnet mean 982 : -0.4104633 
nnet RMSE 982 : 0.1435577 


s: 983 
logit 983 : -0.4540702 
logit mean 983 : -0.4358513 
logit RMSE 983 : 0.06683205 

boosting 983 : -0.4579717 
boosting mean 983 : -0.4928476 
boosting RMSE 983 : 0.1472349 

forest 983 : -0.3608665 
forest mean 983 : -0.384295 
forest RMSE 983 : 0.05343762 

nnet 983 : -0.4645826 
nnet mean 983 : -0.4105183 
nnet RMSE 983 : 0.1434994 


s: 984 
logit 984 : -0.4188217 
logit mean 984 : -0.435834 
logit RMSE 984 : 0.06680077 

boosting 984 : -0.5720984 
boosting mean 984 : -0.4929281 
boosting RMSE 984 : 0.1472623 

forest 984 : -0.4308655 
forest mean 984 : -0.3843423 
forest RMSE 984 : 0.05341952 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 984 : -0.2139468 
nnet mean 984 : -0.4103186 
nnet RMSE 984 : 0.1435491 


s: 985 
logit 985 : -0.5149204 
logit mean 985 : -0.4359143 
logit RMSE 985 : 0.06686719 

boosting 985 : -0.5891148 
boosting mean 985 : -0.4930258 
boosting RMSE 985 : 0.1473108 

forest 985 : -0.4363888 
forest mean 985 : -0.3843952 
forest RMSE 985 : 0.05340498 

nnet 985 : -0.2306585 
nnet mean 985 : -0.4101362 
nnet RMSE 985 : 0.1435776 


s: 986 
logit 986 : -0.383552 
logit mean 986 : -0.4358612 
logit RMSE 986 : 0.06683532 

boosting 986 : -0.2801755 
boosting mean 986 : -0.4928099 
boosting RMSE 986 : 0.1472855 

forest 986 : -0.4363519 
forest mean 986 : -0.3844479 
forest RMSE 986 : 0.05339045 

nnet 986 : -0.4406754 
nnet mean 986 : -0.4101672 
nnet RMSE 986 : 0.1435106 


s: 987 
logit 987 : -0.3892341 
logit mean 987 : -0.4358139 
logit RMSE 987 : 0.06680234 

boosting 987 : -0.3152822 
boosting mean 987 : -0.4926301 
boosting RMSE 987 : 0.1472356 

forest 987 : -0.4103472 
forest mean 987 : -0.3844741 
forest RMSE 987 : 0.05336441 

nnet 987 : -0.3385904 
nnet mean 987 : -0.4100946 
nnet RMSE 987 : 0.1434512 


s: 988 
logit 988 : -0.4549019 
logit mean 988 : -0.4358332 
logit RMSE 988 : 0.06679136 

boosting 988 : -0.5168313 
boosting mean 988 : -0.4926545 
boosting RMSE 988 : 0.147208 

forest 988 : -0.3776831 
forest mean 988 : -0.3844672 
forest RMSE 988 : 0.05334212 

nnet 988 : -0.2550099 
nnet mean 988 : -0.4099377 
nnet RMSE 988 : 0.1434528 


s: 989 
logit 989 : -0.3453219 
logit mean 989 : -0.4357417 
logit RMSE 989 : 0.06678023 

boosting 989 : -0.5648847 
boosting mean 989 : -0.4927276 
boosting RMSE 989 : 0.1472270 

forest 989 : -0.3922241 
forest mean 989 : -0.3844751 
forest RMSE 989 : 0.05331572 

nnet 989 : -0.4445814 
nnet mean 989 : -0.4099727 
nnet RMSE 989 : 0.1433872 


s: 990 
logit 990 : -0.4010438 
logit mean 990 : -0.4357067 
logit RMSE 990 : 0.0667465 

boosting 990 : -0.5817691 
boosting mean 990 : -0.4928175 
boosting RMSE 990 : 0.1472659 

forest 990 : -0.4363808 
forest mean 990 : -0.3845275 
forest RMSE 990 : 0.05330133 

nnet 990 : -0.3982468 
nnet mean 990 : -0.4099609 
nnet RMSE 990 : 0.1433148 


s: 991 
logit 991 : -0.4475742 
logit mean 991 : -0.4357186 
logit RMSE 991 : 0.06672993 

boosting 991 : -0.5795912 
boosting mean 991 : -0.4929051 
boosting RMSE 991 : 0.1473021 

forest 991 : -0.3532344 
forest mean 991 : -0.3844959 
forest RMSE 991 : 0.05329514 

nnet 991 : -0.4446486 
nnet mean 991 : -0.4099959 
nnet RMSE 991 : 0.1432495 


s: 992 
logit 992 : -0.4540982 
logit mean 992 : -0.4357372 
logit RMSE 992 : 0.0667184 

boosting 992 : -0.3865512 
boosting mean 992 : -0.4927979 
boosting RMSE 992 : 0.1472285 

forest 992 : -0.331086 
forest mean 992 : -0.3844421 
forest RMSE 992 : 0.05331319 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 992 : -0.1730126 
nnet mean 992 : -0.409757 
nnet RMSE 992 : 0.1433586 


s: 993 
logit 993 : -0.4174602 
logit mean 993 : -0.4357188 
logit RMSE 993 : 0.0666871 

boosting 993 : -0.4385707 
boosting mean 993 : -0.4927433 
boosting RMSE 993 : 0.1471594 

forest 993 : -0.3621059 
forest mean 993 : -0.3844196 
forest RMSE 993 : 0.0532999 

nnet 993 : -0.6481225 
nnet mean 993 : -0.409997 
nnet RMSE 993 : 0.1435025 


s: 994 
logit 994 : -0.425943 
logit mean 994 : -0.4357089 
logit RMSE 994 : 0.06665862 

boosting 994 : -0.4355259 
boosting mean 994 : -0.4926857 
boosting RMSE 994 : 0.1470897 

forest 994 : -0.3550900 
forest mean 994 : -0.3843901 
forest RMSE 994 : 0.05329213 

nnet 994 : -0.2510574 
nnet mean 994 : -0.4098371 
nnet RMSE 994 : 0.1435081 


s: 995 
logit 995 : -0.4303377 
logit mean 995 : -0.4357035 
logit RMSE 995 : 0.06663206 

boosting 995 : -0.3615695 
boosting mean 995 : -0.4925539 
boosting RMSE 995 : 0.1470208 

forest 995 : -0.4029833 
forest mean 995 : -0.3844088 
forest RMSE 995 : 0.05326542 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 995 : -0.1596691 
nnet mean 995 : -0.4095857 
nnet RMSE 995 : 0.1436382 


s: 996 
logit 996 : -0.4754587 
logit mean 996 : -0.4357435 
logit RMSE 996 : 0.06664151 

boosting 996 : -0.3937858 
boosting mean 996 : -0.4924548 
boosting RMSE 996 : 0.1469471 

forest 996 : -0.3584796 
forest mean 996 : -0.3843827 
forest RMSE 996 : 0.05325493 

nnet 996 : -0.3245447 
nnet mean 996 : -0.4095003 
nnet RMSE 996 : 0.1435860 


s: 997 
logit 997 : -0.4429 
logit mean 997 : -0.4357506 
logit RMSE 997 : 0.06662193 

boosting 997 : -0.5236746 
boosting mean 997 : -0.4924861 
boosting RMSE 997 : 0.1469256 

forest 997 : -0.3490122 
forest mean 997 : -0.3843473 
forest RMSE 997 : 0.05325271 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.

nnet 997 : -0.1714777 
nnet mean 997 : -0.4092616 
nnet RMSE 997 : 0.1436963 


s: 998 
logit 998 : -0.5042689 
logit mean 998 : -0.4358193 
logit RMSE 998 : 0.0666703 

boosting 998 : -0.511325 
boosting mean 998 : -0.492505 
boosting RMSE 998 : 0.1468943 

forest 998 : -0.4386955 
forest mean 998 : -0.3844017 
forest RMSE 998 : 0.05324011 

nnet 998 : -0.5114379 
nnet mean 998 : -0.4093639 
nnet RMSE 998 : 0.1436676 


s: 999 
logit 999 : -0.4331951 
logit mean 999 : -0.4358167 
logit RMSE 999 : 0.0666452 

boosting 999 : -0.4795243 
boosting mean 999 : -0.492492 
boosting RMSE 999 : 0.1468423 

forest 999 : -0.372042 
forest mean 999 : -0.3843893 
forest RMSE 999 : 0.05322081 

nnet 999 : -0.1351076 
nnet mean 999 : -0.4090894 
nnet RMSE 999 : 0.1438401 


s: 1000 
logit 1000 : -0.5442998 
logit mean 1000 : -0.4359251 
logit RMSE 1000 : 0.06676798 

boosting 1000 : -0.5140792 
boosting mean 1000 : -0.4925135 
boosting RMSE 1000 : 0.1468132 

forest 1000 : -0.4012833 
forest mean 1000 : -0.3844062 
forest RMSE 1000 : 0.05319421 

nnet 1000 : -0.3179940 
nnet mean 1000 : -0.4089983 
nnet RMSE 1000 : 0.1437915 
There were 50 or more warnings (use warnings() to see the first 50)
> 
> 
> rm(sdta)
> save.image("RData.sims.F.nobs1000",compress="bzip2")
> 
> proc.time()
    user   system  elapsed 
45279.17     8.91 45783.32 
